U.S. patent application number 14/444925 was filed with the patent office on 2015-01-22 for look ahead of links/alter links.
The applicant listed for this patent is Searete LLC. Invention is credited to Gary W. Flake, William Gates, Roderick A. Hyde, Edward K.Y. Jung, Royce A. Levien, Robert W. Lord, Mark A. Malamud, Richard F. Rashid, John D. Rinaldo, Jr., Clarence T. Tegreene, Charles Whitmer, Lowell L. Wood, JR..
Application Number | 20150026679 14/444925 |
Document ID | / |
Family ID | 50149204 |
Filed Date | 2015-01-22 |
United States Patent
Application |
20150026679 |
Kind Code |
A1 |
Flake; Gary W. ; et
al. |
January 22, 2015 |
Look Ahead of Links/Alter Links
Abstract
A computationally-implemented method includes obtaining data
from a data source, determining an acceptability of an effect of
the data on at least a part of a real machine at least in part via
one or more virtual machine representations of the at least a part
of the a real machine, and controlling at least one operation of
the at least one real machine based on the determining an
acceptability of a content of the data.
Inventors: |
Flake; Gary W.; (Bellevue,
WA) ; Gates; William; (Medina, WA) ; Hyde;
Roderick A.; (Redmond, WA) ; Jung; Edward K.Y.;
(Bellevue, WA) ; Levien; Royce A.; (Lexington,
MA) ; Lord; Robert W.; (Seattle, WA) ;
Malamud; Mark A.; (Seattle, WA) ; Rashid; Richard
F.; (Redmond, WA) ; Rinaldo, Jr.; John D.;
(Bellevue, WA) ; Tegreene; Clarence T.; (Mercer
Island, WA) ; Whitmer; Charles; (North Bend, WA)
; Wood, JR.; Lowell L.; (Bellevue, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Searete LLC |
Bellevue |
WA |
US |
|
|
Family ID: |
50149204 |
Appl. No.: |
14/444925 |
Filed: |
July 28, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13914279 |
Jun 10, 2013 |
8793616 |
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14444925 |
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12005064 |
Dec 21, 2007 |
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13914279 |
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12005637 |
Dec 27, 2007 |
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12005064 |
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12074855 |
Mar 6, 2008 |
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12005637 |
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12154148 |
May 20, 2008 |
8473836 |
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12074855 |
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12154423 |
May 22, 2008 |
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12154148 |
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12154436 |
May 22, 2008 |
8468440 |
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12154423 |
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12214784 |
Jun 20, 2008 |
8489981 |
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12154436 |
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12215695 |
Jun 27, 2008 |
8495486 |
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12214784 |
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Current U.S.
Class: |
718/1 |
Current CPC
Class: |
G06F 2009/45562
20130101; G06F 9/45533 20130101; G06F 2009/45579 20130101; G06F
9/45558 20130101 |
Class at
Publication: |
718/1 |
International
Class: |
G06F 9/455 20060101
G06F009/455 |
Claims
1. A computationally-implemented method comprising: obtaining data
from a data source; determining an acceptability of an effect of
the data on at least a part of a real machine at least in part via
one or more virtual machine representations of the at least a part
of the real machine; and controlling at least one operation of the
at least one real machine based on the determining an acceptability
of a content of the data.
2. The computationally-implemented method of claim 1, wherein the
obtaining data from a data source includes: determining a content
type of the data.
3-5. (canceled)
6. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: examining at least a portion of the data to locate
references to additional content.
7-8. (canceled)
9. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of a real machine at least in part via one or more
virtual machine representations of the at least a part of the real
machine at least partially resident within a real machine.
10. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of a real machine at least in part via one or more
virtual machine representations of the at least a part of the real
machine at least partially non-resident within a real machine.
11. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of at least a portion of content of a real
machine.
12. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of at least a portion of software of a real
machine.
13. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of at least a portion of hardware of a real
machine.
14. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of at least a portion of an operating system of a
real machine.
15. The computationally implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of a real machine including at least a portion of a
computing device.
16. The computationally implemented method of claim 1, wherein
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of the data on
at least a part of at least one peripheral device.
17. The computationally implemented method of claim 16, wherein the
determining an acceptability of an effect of the data on at least a
part of at least one peripheral device includes: determining an
acceptability of an effect of the data on at least a part of at
least one of a printer, a fax machine, a peripheral memory device,
a network adapter, a music player, a cellular telephone, a data
acquisition device, or a device actuator.
18. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining a state of one or more virtual machine
representations prior to loading at least a portion of data.
19. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining a state of one or more virtual machine
representations subsequent to loading at least a portion of
data.
20. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining a state change of one or more virtual machine
representations between a state prior to loading at least a portion
of data and a state after loading the at least a portion of
data.
21. The computationally-implemented method of claim 20, wherein the
determining a state change of one or more virtual machine
representations between a state prior to loading at least a portion
of data and a state after loading the at least a portion of data
includes: determining whether a state change of the one or more
virtual machine representations is an undesirable state change
based on one or more end-user specified preferences.
22. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of content of
the data in response to at least one user setting.
23-32. (canceled)
33. The computationally-implemented method of claim 1, wherein the
determining an acceptability of an effect of the data on at least a
part of a real machine at least in part via one or more virtual
machine representations of the at least a part of the real machine
includes: determining an acceptability of an effect of content of
the data in response to at least one privacy related setting.
34-41. (canceled)
42. The computationally-implemented method of claim 1, wherein the
controlling at least one operation of the at least one real machine
based on the determining an acceptability of a content of the data
includes: displaying at least a portion of data.
43. The computationally-implemented method of claim 1, wherein the
controlling at least one operation of the at least one real machine
based on the determining an acceptability of a content of the data
includes: not displaying at least a portion of data.
44. The computationally-implemented method of claim 1, wherein the
controlling at least one operation of the at least one real machine
based on the determining an acceptability of a content of the data
includes: displaying a modified version of data.
45. The computationally-implemented method of claim 44, wherein the
displaying a modified version of data includes: obfuscating an
objectionable data portion.
46. The computationally-implemented method of claim 44, wherein the
displaying a modified version of data includes: anonymizing an
objectionable data portion.
47. The computationally-implemented method of claim 44, wherein the
displaying a modified version of data includes: at least one of
removing, altering or replacing an objectionable data portion.
48. The computationally-implemented method of claim 44, wherein the
removing, altering or replacing an objectionable data portion
includes: displaying a data portion consistent with at least one
user-related setting.
49-56. (canceled)
57. The computationally-implemented method of claim 1, wherein the
controlling at least one operation of the at least one real machine
based on the determining an acceptability of a content of the data
includes: redirecting to alternative data different than the
data.
58. The computationally-implemented method of claim 57, wherein the
redirecting to alternative data different than the data includes:
automatically redirecting to alternative data.
59. The computationally-implemented method of claim 57, wherein the
redirecting to alternative data different than the data includes:
providing a list of selectable alternative data options.
60. The computationally-implemented method of claim 57, wherein the
redirecting to alternative data different than the data includes:
displaying alternative data consistent with a privacy setting.
61. The computationally-implemented method of claim 57, wherein the
redirecting to alternative data different than the data includes:
displaying alternative data consistent with a user setting.
62-63. (canceled)
64. The computationally-implemented method of claim 57, wherein the
redirecting to alternative data different than the data includes:
displaying alternative data consistent with a user history.
65-69. (canceled)
70. A system comprising: at least one computing device; and one or
more instructions that, when implemented in the computing device,
configure the at least one computing device for: obtaining data
from a data source; determining an acceptability of an effect of
the data on at least a part of a real machine at least in part via
one or more virtual machine representations of the at least a part
of the real machine; and controlling at least one operation of the
at least one real machine based on the determining an acceptability
of a content of the data.
71-138. (canceled)
139. A computationally-implemented system comprising: circuitry for
obtaining data from a data source; circuitry for determining an
acceptability of an effect of the data on at least a part of a real
machine at least in part via one or more virtual machine
representations of the at least a part of the real machine; and
circuitry for controlling at least one operation of the at least
one real machine based on the determining an acceptability of a
content of the data.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is related to and claims the benefit
of the earliest available effective filing date(s) from the
following listed application(s) (the "Related Applications") (e.g.,
claims earliest available priority dates for other than provisional
patent applications or claims benefits under 35 USC .sctn.119(e)
for provisional patent applications, for any and all parent,
grandparent, great-grandparent, etc. applications of the Related
Application(s)).
RELATED APPLICATIONS
[0002] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake as the first named inventor, filed 21 Dec. 2007,
application Ser. No. 12/005,064, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0003] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake as the first named inventor, filed Dec. 27, 2007,
application Ser. No. 12/005,637, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0004] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed 21 Dec. 2007,
application Ser. No. 12/005,064, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0005] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed Dec. 27, 2007,
application Ser. No. 12/005,637, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0006] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed Mar. 6, 2008,
application Ser. No. 12/074,855, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0007] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed May 20, 2008,
application Ser. No. 12/154,148, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0008] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed May 22, 2008,
application Ser. No. 12/154,423, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0009] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed May 22, 2008,
application Ser. No. 12/154,436, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0010] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed Jun. 20, 2008,
application Ser. No. 12/214,784, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0011] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed Jun. 27, 2008,
application Ser. No. 12/215,695, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0012] For purposes of the USPTO extra-statutory requirements, the
present application constitutes a continuation-in-part of U.S.
patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS, naming
Gary W. Flake; William H. Gates, III; Roderick A. Hyde; Edward K.
Y. Jung; Royce A. Levien; Robert W. Lord; Mark A. Malamud; Richard
F. Rashid; John D. Rinaldo, Jr.; Clarence T. Tegreene; Charles
Whitmer; and Lowell L. Wood, Jr. as inventors, filed Jun. 10, 2013,
application Ser. No. 13/914,279, which is currently co-pending, or
is an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0013] The United States Patent Office (USPTO) has published a
notice to the effect that the USPTO's computer programs require
that patent applicants reference both a serial number and indicate
whether an application is a continuation or continuation-in-part.
Stephen G. Kunin, Benefit of Prior-Filed Application, USPTO
Official Gazette Mar. 18, 2003, available at
http://www.uspto.gov/web/offices/com/sol/og/2003/week11/patbene.htm.
The present Applicant has provided above a specific reference to
the application(s) from which priority is being claimed as recited
by statute. Applicant understands that the statute is unambiguous
in its specific reference language and does not require either a
serial number or any characterization, such as "continuation" or
"continuation-in-part," for claiming priority to U.S. patent
applications. Notwithstanding the foregoing, Applicant understands
that the USPTO's computer programs have certain data entry
requirements, and hence Applicant is designating the present
application as a continuation-in-part of its parent applications as
set forth above, but expressly points out that such designations
are not to be construed in any way as any type of commentary and/or
admission as to whether or not the present application contains any
new matter in addition to the matter of its parent
application(s).
[0014] All subject matter of the Related Application and of any and
all parent, grandparent, great-grandparent, etc. applications of
the Related Applications is incorporated herein by reference to the
extent such subject matter is not inconsistent herewith.
BACKGROUND
[0015] Web sites often contain links to other web sites enabling a
user to navigate from one web site to another. Certain links may
contain data that may compromise security and/or privacy. Certain
links may contain data that a user may not desire to view.
SUMMARY
[0016] A computationally implemented method may include, but is not
limited to: obtaining at least a portion of data from a data
source; determining an acceptability of an effect of the data on at
least one virtual machine representation of at least a part of a
real machine; and controlling one or more functions of the at least
one real machine based on the determining an acceptability of an
effect of the data on at least one virtual machine representation
of at least a part of a real machine. In addition to the foregoing,
other computationally implemented method aspects are described in
the claims, drawings, and text forming a part of the present
disclosure.
[0017] In one or more various aspects, related systems include but
are not limited to circuitry and/or programming for effecting the
herein referenced method aspects; the circuitry and/or programming
can be virtually any combination of hardware, software, and/or
firmware configured to effect the herein referenced method aspects
depending upon the design choices of the system designer.
[0018] A computationally implemented system includes, but is not
limited to: means for obtaining at least a portion of data from a
data source; means for determining a content of the data; means for
determining an acceptability of an effect of content of the data at
least in part via at least two virtual machine representations of
at least a part of a real machine having at least one end-user
specified preference, at least one of the at least two virtual
machine representations operating at least in part on an individual
core of a multi-core system; and means for displaying at least one
data display option based on the determining an acceptability of a
content of the data. In addition to the foregoing, other system
aspects are described in the claims, drawings, and text forming a
part of the present disclosure.
[0019] A computationally implemented system includes, but is not
limited to: circuitry for obtaining at least a portion of data from
a data source; circuitry for determining a content of the data;
circuitry for determining an acceptability of an effect of content
of the data at least in part via at least two virtual machine
representations of at least a part of a real machine having at
least one end-user specified preference, at least one of the at
least two virtual machine representations operating at least in
part on an individual core of a multi-core system; and circuitry
for displaying at least one data display option based on the
determining an acceptability of a content of the data. In addition
to the foregoing, other system aspects are described in the claims,
drawings, and text forming a part of the present disclosure.
[0020] The foregoing summary is illustrative only and is not
intended to be in any way limiting. In addition to the illustrative
aspects, embodiments, and features described above, further
aspects, embodiments, and features will become apparent by
reference to the drawings and the following detailed
description.
BRIEF DESCRIPTION OF THE FIGURES
[0021] FIG. 1A illustrates an exemplary environment in which one or
more technologies may be implemented.
[0022] FIG. 1B illustrates an operational view of a real machine in
which at least a portion of the system illustrated in FIG. 1A has
been implemented.
[0023] FIG. 1C illustrates an operational view of a real machine in
which at least a portion of the system illustrated in FIG. 1A has
been implemented.
[0024] FIG. 1D illustrates an operational view of a real machine in
which at least a portion of the system illustrated in FIG. 1A has
been implemented.
[0025] FIG. 2 illustrates an operational flow representing example
operations related to providing acceptable data to a real
machine.
[0026] FIG. 3 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0027] FIG. 4 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0028] FIG. 5 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0029] FIG. 6 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0030] FIG. 7 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0031] FIG. 8 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0032] FIG. 9 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0033] FIG. 10 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0034] FIG. 11 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0035] FIG. 12 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0036] FIG. 13 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0037] FIG. 14 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0038] FIG. 15 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0039] FIG. 16 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0040] FIG. 17 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0041] FIG. 18 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0042] FIG. 19 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0043] FIG. 20 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0044] FIG. 21 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0045] FIG. 22 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0046] FIG. 23 illustrates an alternative embodiment of the
operational flow of FIG. 2.
[0047] FIG. 24 illustrates an operational flow representing example
operations related to providing acceptable data to a real
machine.
[0048] FIG. 25 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0049] FIG. 26 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0050] FIG. 27 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0051] FIG. 28 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0052] FIG. 29 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0053] FIG. 30 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0054] FIG. 31 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0055] FIG. 32 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0056] FIG. 33 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0057] FIG. 34 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0058] FIG. 35 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0059] FIG. 36 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0060] FIG. 37 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0061] FIG. 38 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0062] FIG. 39 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0063] FIG. 40 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0064] FIG. 41 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0065] FIG. 42 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0066] FIG. 43 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0067] FIG. 44 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0068] FIG. 45 illustrates an alternative embodiment of the
operational flow of FIG. 24.
[0069] FIG. 46 illustrates an operational flow representing example
operations related to providing acceptable data to a real
machine.
[0070] FIG. 47 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0071] FIG. 48 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0072] FIG. 49 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0073] FIG. 50 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0074] FIG. 51 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0075] FIG. 52 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0076] FIG. 53 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0077] FIG. 54 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0078] FIG. 55 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0079] FIG. 56 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0080] FIG. 57 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0081] FIG. 58 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0082] FIG. 59 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0083] FIG. 60 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0084] FIG. 61 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0085] FIG. 62 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0086] FIG. 63 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0087] FIG. 64 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0088] FIG. 65 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0089] FIG. 66 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0090] FIG. 67 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0091] FIG. 68 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0092] FIG. 69 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0093] FIG. 70 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0094] FIG. 71 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0095] FIG. 72 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0096] FIG. 73 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0097] FIG. 74 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0098] FIG. 75 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0099] FIG. 76 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0100] FIG. 77 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0101] FIG. 78 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0102] FIG. 79 illustrates an alternative embodiment of the
operational flow of FIG. 46.
[0103] FIG. 80 illustrates an operational flow representing example
operations related to providing acceptable data to a real
machine.
[0104] FIG. 81 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0105] FIG. 82 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0106] FIG. 83 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0107] FIG. 84 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0108] FIG. 85 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0109] FIG. 86 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0110] FIG. 87 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0111] FIG. 88 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0112] FIG. 89 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0113] FIG. 90 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0114] FIG. 91 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0115] FIG. 92 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0116] FIG. 93 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0117] FIG. 94 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0118] FIG. 95 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0119] FIG. 96 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0120] FIG. 97 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0121] FIG. 98 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0122] FIG. 99 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0123] FIG. 100 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0124] FIG. 101 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0125] FIG. 102 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0126] FIG. 103 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0127] FIG. 104 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0128] FIG. 105 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0129] FIG. 106 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0130] FIG. 107 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0131] FIG. 108 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0132] FIG. 109 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0133] FIG. 110 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0134] FIG. 111 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0135] FIG. 112 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0136] FIG. 113 illustrates an alternative embodiment of the
operational flow of FIG. 80.
[0137] FIG. 114 illustrates an operational flow representing
example operations related to providing acceptable data to a real
machine.
[0138] FIG. 115 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0139] FIG. 116 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0140] FIG. 117 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0141] FIG. 118 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0142] FIG. 119 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0143] FIG. 120 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0144] FIG. 121 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0145] FIG. 122 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0146] FIG. 123 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0147] FIG. 124 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0148] FIG. 125 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0149] FIG. 126 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0150] FIG. 127 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0151] FIG. 128 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0152] FIG. 129 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0153] FIG. 130 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0154] FIG. 131 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0155] FIG. 132 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0156] FIG. 133 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0157] FIG. 134 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0158] FIG. 135 illustrates an alternative embodiment of the
operational flow of FIG. 114.
[0159] FIG. 136 illustrates an operational flow representing
example operations related to providing acceptable data to a real
machine.
[0160] FIG. 137 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0161] FIG. 138 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0162] FIG. 139 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0163] FIG. 140 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0164] FIG. 141 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0165] FIG. 142 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0166] FIG. 143 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0167] FIG. 144 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0168] FIG. 145 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0169] FIG. 146 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0170] FIG. 147 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0171] FIG. 148 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0172] FIG. 149 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0173] FIG. 150 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0174] FIG. 151 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0175] FIG. 152 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0176] FIG. 153 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0177] FIG. 154 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0178] FIG. 155 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0179] FIG. 156 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0180] FIG. 157 illustrates an alternative embodiment of the
operational flow of FIG. 136.
[0181] FIG. 158 illustrates an operational flow representing
example operations related to providing acceptable data to a real
machine.
[0182] FIG. 159 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0183] FIG. 160 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0184] FIG. 161 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0185] FIG. 162 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0186] FIG. 163 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0187] FIG. 164 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0188] FIG. 165 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0189] FIG. 166 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0190] FIG. 167 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0191] FIG. 168 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0192] FIG. 169 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0193] FIG. 170 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0194] FIG. 171 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0195] FIG. 172 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0196] FIG. 173 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0197] FIG. 174 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0198] FIG. 175 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0199] FIG. 176 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0200] FIG. 177 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0201] FIG. 178 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0202] FIG. 179 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0203] FIG. 180 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0204] FIG. 181 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0205] FIG. 182 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0206] FIG. 183 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0207] FIG. 184 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0208] FIG. 185 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0209] FIG. 186 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0210] FIG. 187 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0211] FIG. 188 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0212] FIG. 189 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0213] FIG. 190 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0214] FIG. 191 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0215] FIG. 192 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0216] FIG. 193 illustrates an alternative embodiment of the
operational flow of FIG. 158.
[0217] FIG. 194 illustrates an operational flow representing
example operations related to providing acceptable data to a real
machine.
[0218] FIG. 195 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0219] FIG. 196 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0220] FIG. 197 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0221] FIG. 198 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0222] FIG. 199 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0223] FIG. 200 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0224] FIG. 201 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0225] FIG. 202 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0226] FIG. 203 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0227] FIG. 204 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0228] FIG. 205 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0229] FIG. 206 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0230] FIG. 207 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0231] FIG. 208 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0232] FIG. 209 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0233] FIG. 210 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0234] FIG. 211 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0235] FIG. 212 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0236] FIG. 213 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0237] FIG. 214 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0238] FIG. 215 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0239] FIG. 216 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0240] FIG. 217 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0241] FIG. 218 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0242] FIG. 219 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0243] FIG. 220 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0244] FIG. 221 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0245] FIG. 222 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0246] FIG. 223 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0247] FIG. 224 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0248] FIG. 225 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0249] FIG. 226 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0250] FIG. 227 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0251] FIG. 228 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0252] FIG. 229 illustrates an alternative embodiment of the
operational flow of FIG. 194.
[0253] FIG. 230 illustrates an operational flow representing
example operations related to providing acceptable data to a real
machine.
[0254] FIG. 231 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0255] FIG. 232 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0256] FIG. 233 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0257] FIG. 234 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0258] FIG. 235 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0259] FIG. 236 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0260] FIG. 237 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0261] FIG. 238 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0262] FIG. 239 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0263] FIG. 240 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0264] FIG. 241 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0265] FIG. 242 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0266] FIG. 243 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0267] FIG. 244 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0268] FIG. 245 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0269] FIG. 246 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0270] FIG. 247 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0271] FIG. 248 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0272] FIG. 249 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0273] FIG. 250 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0274] FIG. 251 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0275] FIG. 252 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0276] FIG. 253 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0277] FIG. 254 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0278] FIG. 255 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0279] FIG. 256 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0280] FIG. 257 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0281] FIG. 258 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0282] FIG. 259 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0283] FIG. 260 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0284] FIG. 261 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0285] FIG. 262 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0286] FIG. 263 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0287] FIG. 264 illustrates an alternative embodiment of the
operational flow of FIG. 30.
[0288] FIG. 265 illustrates an alternative embodiment of the
operational flow of FIG. 30.
DETAILED DESCRIPTION
[0289] In the following detailed description, reference is made to
the accompanying drawings, which form a part hereof. In the
drawings, similar symbols typically identify similar components,
unless context dictates otherwise. The illustrative embodiments
described in the detailed description, drawings, and claims are not
meant to be limiting. Other embodiments may he utilized, and other
changes may be made, without departing from the spirit or scope of
the subject matter presented here.
[0290] Referring to FIG. 1A, a system 100 related to looking ahead
for data is illustrated. The system 100 may include a data
retreiver engine 102, a data content determination engine 104, an
Effect of content acceptability determination engine 106, and a
data content provider engine 108. Data content determination engine
104 may include a database examination engine 112, a data
transverser engine 114, and a local data examination engine 116.
Effect of content acceptability determination engine 106 may
include a virtual machine module 118 including one or more virtual
machines 11, 12, and 13, database examination engine 112, a data
transverser engine 114, a local data examination engine 116 and a
user preference database 120. Data content provider engine 108 may
include a data modification engine 122 that may further include a
data obfuscation engine 124 and a data anonymization engine 126.
Data content provider engine 108 may also include a data
redirection engine 128.
[0291] FIG. 1B illustrates an operational view of real machine 130
(e.g., a desktop, notebook, or other type computing system,
including or excluding one or more peripheral devices) in which at
least a portion of system 100 (FIG. 1A) has been implemented.
System 100 may be at least partially implemented in a multi-core
processor at least partially resident within real machine 130
(e.g., one or more virtual machines of virtual machine module 118
at least partially respectively implemented on one or more cores of
a multi-core processor of real machine 130). System 100 may also be
at least partially implemented in a multi-core processor at least
partially non-resident within real machine 130 (e.g., one or more
virtual machines of virtual machine module 118 at least partially
respectively implemented on one or more cores of a multi-core
processor of a hosting site/machine/system physically distal from
real machine 130).
[0292] FIG. 1B illustrates real machine 130 containing data 110
(e.g., a Web page) containing Link 1, Link 2, and Link 3. FIG. 1B
illustrates an example in which at least a part of system 100
traverses Link 1, Link 2, and Link 3 of data 110 via virtual
machines 11, 12, and 13, which may be virtual machine
representations of real machine 130. In some instances, such
virtual machine traversals are utilized to prospectively determine
what might happen should real machine 130 be used to traverse such
links. For example, determining how such traversal(s) might compare
to one or more user-associated preferences of real machine 130
(e.g., that user 10 prefers to visit sites having content
acceptable to a defined organization, such as a government; that
user 10 prefers not to visit sites having malware or spyware; that
user 10 prefers not to visit sites that reset real machine hardware
options (e.g., audio/visual peripherals); that user 10 prefers not
to visit sites that reset real machine software options (e.g.,
proxy servers); etc.). User-associated preferences of real machine
130 may be stored in user preference database 120 (FIG. 1A) of
Effect of content acceptability determination engine 106 (FIG. 1A).
User preference database 120 may contain user preferences with
respect to content of the real machine 130, hardware of the real
machine 130, software of the real machine 130, and an operating
system of the real machine 130. User preference database 120 may be
in communication with virtual machine module 118 (FIG. 1A).
Specifically, virtual machine module 118 (FIG. 1A) may receive user
preference database information from user preference database 120
(FIG. 1A) and spawn a copy of at least a portion of user preference
database 120 (FIG. 1A) on at least one of virtual machines 11, 12,
and/or 13.
[0293] FIG. 1B illustrates virtual machine 11. Virtual machine 11
may be illustrated as included in virtual machine module 118 (FIG.
1A) of Effect of content acceptability determination engine 106
(FIG. 1A). FIG. 1B illustrates virtual machine 11 encompassing a
virtual machine representation of real machine 130, post (e.g.,
subsequent to) activation of Link 1 (e.g., as at least a part of
real machine 130 would exist had link 1 actually been traversed on
real machine 130). FIG. 1B illustrates virtual machine 11 including
a virtual machine representation of the content of the real machine
130 post activation of Link 1. Examples of such content include a
movie, music file, a script (e.g., Java script or Active X
control), a markup language, an email, etc. downloaded onto real
machine 130 from one or more sources associated with
activation/traversal of Link 1.
[0294] FIG. 1B also illustrates virtual machine 11 including a
virtual machine representation of software (e.g., a state of
software) of the real machine 130 post (e.g., subsequent to)
activation of Link 1. Examples of such software might include a
commercial word processing program or suite of programs (e.g.,
Microsoft.RTM. Office for Windows), an open source Web browser
(e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up (e.g., an
executing JavaScript.TM. and/or data obtained by same via an
XML-like scheme), or a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware program (e.g., such as those of Symantec
Corporation or McAfee, Inc.), etc.
[0295] FIG. 1B also illustrates virtual machine 11 including a
virtual machine representation of hardware (e.g., a state of the
hardware) of the real machine 130 post activation of Link 1.
Examples of such hardware might include all or part of a chipset
(e.g., data processor and/or graphics processor chipsets such as
those of Intel Corporation and/or Nvidia Corporation), a memory
chip (e.g., flash memory and/or random access memories such as
those of Sandisk Corporation and/or Samsung Electronics, Co., LTD),
a data bus, a hard disk (e.g., such as those of Seagate Technology,
LLC), a network adapter (e.g., wireless and/or wired LAN adapters
such as those of Linksys- and/or CiscoTechnology, Inc.), printer, a
removable drive (e.g., flash drive), a cell phone, etc.
[0296] FIG. 1B also illustrates virtual machine 11 including a
virtual machine representation of an operating system (e.g., a
state of an operating system and/or network operating system) of
the real machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
Microsoft.RTM. Windows 2000, Unix, Linux, etc.) and/or a network
operating system (e.g., the Internet Operating System available
from Cisco Technology, Inc. Netware.RTM. available from Novell,
Inc., and/or Solaris available from Sun Microsystems, Inc.).
[0297] FIG. 1B also illustrates that virtual machine 11 may run on
core 11 of a multi-core processor. In addition to the herein, those
skilled in the art will appreciate that the virtual machine
representations discussed herein are not limited to specific
examples described, but instead include any components of real
machine 130 as such might be understood in the art. Examples of the
foregoing would include firmware, logic associated with display
units, logic associated with robotics, application specific
integrated circuits, etc.
[0298] As noted, in some instances system 100 may traverse (e.g.,
view) links of data 110 via one or more virtual machine
representations of at least a part of real machine 130.
Accordingly, FIG. 1B illustrates virtual machine 12 encompassing a
virtual machine representation of real machine 130 (e.g., one or
more states of one or more components associated with real machine
130), post activation of Link 2. FIG. 1B illustrates virtual
machine 12 at least partly running on core 12 of a multi-core
processor. Virtual machine module 118 (FIG. 1A) of Effect of
content acceptability determination engine 106 (FIG. 1A) may be
illustrated to include virtual machine 12. FIG. 1B also illustrates
virtual machine 12 may include a virtual machine representation of
content (e.g., a video) of real machine 130 post activation of Link
2, a virtual machine representation of software (e.g., Microsoft
Office for Windows) of real machine 130 post activation of Link 2,
a virtual machine representation of hardware (e.g., the circuitry
or processor of the real machine) of real machine 130 post
activation of Link 2, and a virtual machine representation of
operating system (e.g., Microsoft Windows 2000, XP, Vista) of real
machine 130 post activation-of Link 2.
[0299] As noted, in some instances system 100 may traverse links of
data 110 via one or more virtual machine representations of at
least a part of real machine 130. Accordingly, FIG. 1B illustrates
virtual machine 13 encompassing a virtual machine representation of
real machine 130, post activation of Link 3 (e.g., representative
of one or more states of one or more hardware/software/firmware
components of/resident within real machine 130). The foregoing
constitutes one example of how system 100 may use virtual machine
13 to traverse Link 3 (e.g., a link relating to a list of or links
to information on architectural building styles). Virtual machine
module 118 (FIG. 1A) of Effect of content acceptability
determination engine 106 (FIG. 1A) may include virtual machine 13.
FIG. 1B further illustrates virtual machine 13 may include a
virtual machine representation of the content (e.g., a markup
language) of the real machine 130 post activation of Link 3, a
virtual machine representation of the software (e.g., Unix) of the
real machine 130 post activation of Link 3, a virtual machine
representation of the hardware (e.g., a hard disk) of the real
machine 130 post activation of Link 3, and a virtual machine
representation of the operating system (e.g., Solaris Operating
System) of the real machine 130 post activation of Link 3. FIG. 1B
illustrates that virtual machine 13 may be run on core 13 of a
multi-core processor.
[0300] Upon traversal of links 1, 2, and 3 by virtual machines 11,
12, and 13, respectively, each of virtual machines 11, 12, and 13
may determine whether an effect of the data content is acceptable
to a user based on a user's preferences. At least one of virtual
machines 11, 12, and/or 13 may compare the traversed data to one or
more user preferences stored in a user preference database 120
(FIG. 1A). User preference database information may be communicated
to virtual machine module 118 (FIG. 1A) and a copy of at least a
portion of user preference database 120 may be spawned (e.g.,
generated) on at least one of virtual machines 11, 12, and/or 13.
Virtual machines 11, 12, and 13 may communicate the results of a
respective comparison of activation of a link (e.g., loading at
least a portion of a link's content onto a virtual machine 11, 12,
13) to a user preference (e.g., a preference not to load malware
onto a user's real machine) to virtual machine module 118 (FIG.
1A). Virtual machine module 118 (FIG. 1A) may communicate the
results of a comparison of activation of a link to a user
preference to Effect of content acceptability determination engine
106 (FIG. 1A). Effect of content acceptability determination engine
106 may communicate the comparison to the data content provider
engine 108 (FIG. 1A). The data content provider engine 108 may then
provide the results (e.g., one or more web links approved for
viewing) to a real machine 130 (e.g., a computing device with or
without associated peripherals) that may be viewable by a user 10
on a display.
[0301] FIG. 1C illustrates a partial follow-on operational view of
real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1. In the example shown, the content is depicted
as data 110 having Link 4, Link 5, and Link 6. As a specific
example, data 110 could be a Web page containing embedded Link 4 to
an advertisement, Link 5 to a video file, and Link 6 to a still
image file.
[0302] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0303] Upon traversal of links 4, 5, and 6 by virtual machines 21,
22, and 23, respectively, each of virtual machines 21, 22, and 23
may determine whether an effect of the data content is acceptable
to a user based on a user's preferences. Virtual machines 21, 22,
and 23 may compare the traversed data to one or more user
preferences stored in a user preference database 120 (FIG. 1A). As
previously described, user preference database information may be
communicated to virtual machine module 118 (FIG. 1A) and a copy of
at least a portion of user preference database 120 may be spawned
(e.g., generated) on at least one of virtual machines 11, 12,
and/or 13. Virtual machine 11 may then communicate user preference
database information to each of virtual machines 21, 22, and 23,
and a copy of a user preference database 120 (FIG. 1A) may be
spawned on each of virtual machines 21, 22, and 23. Virtual
machines 21, 22, and 23 may communicate the results of a respective
comparison of activation of a link (e.g., loading at least a
portion of a link's content onto a virtual machine 21, 22, and/or
23) to a user preference (e.g., a preference to prevent
installation of a rootkit onto a user's real machine) to virtual
machine 11. Virtual machine 11 may communicate the results of a
comparison to virtual machine module 118 (FIG. 1A). Virtual machine
module 118 (FIG. 1A) may communicate the results of a comparison of
activation of a link to a user preference to effect of content
acceptability determination engine 106 (FIG. 1A). Effect of content
acceptability determination engine 106 may communicate the
comparison to the data content provider engine 108 (FIG. 1A). The
data content provider engine 108 may then provide the results
(e.g., one or more web links approved for viewing) to a real
machine 130 (e.g., a computing device with or without associated
peripherals) that may be viewable by a user 10 on a display.
[0304] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.,
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Link 4 via a virtual machine representation of real
machine 130 encompassed within virtual machine 21. Accordingly,
FIG. 1C illustrates virtual machine 21 including a virtual machine
representation of content (e.g., a movie, web page, music file,
etc.) of the real machine 130 post sequential activation of Link 1
then Link 4, a virtual machine representation of the software
(e.g., Windows Media Player, Apple's Quicktime Player, etc.) of the
real machine 130 post sequential activation of Link 1 then Link 4,
a virtual machine representation of the hardware (e.g., the
circuitry or processor of the real machine) of the real machine 130
post sequential activation of Link 1 then Link 4, and a virtual
machine representation of the operating system (e.g., Linux) of the
real machine 130 post sequential activation of Link 1 then Link
4.
[0305] FIG. 1C illustrates virtual machine 22 encompassing a
virtual machine representation of real machine 130 post (e.g.,
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 5 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 22 may be run on
core 32 of a multi-core processor. FIG. 1C illustrates system 100
traversing Link 5 via a virtual machine representation of real
machine 130 encompassed within virtual machine 22. Accordingly,
FIG. 1C illustrates virtual machine 22 including a virtual machine
representation of content (e.g., a graphical image, a text file, an
email, etc.) of the real machine 130 post (e.g., subsequent to)
sequential activation of Link 1 then Link 5, a virtual machine
representation of software (e.g., an AJAX mashup) of the real
machine 130 post sequential activation of Link 1 then Link 5, a
virtual machine representation of hardware (e.g., a network
adapter) of the real machine 130 post sequential activation of Link
1 then Link 5, and a virtual machine representation of an operating
system (e.g., Mac OS/X) of the real machine 130 post sequential
activation of Link 1 then Link 5.
[0306] FIG. 1C illustrates virtual machine 23 may be a virtual
machine representation of real machine 130 post (e.g., subsequent
to) sequential activation of Link 1 (e.g., FIG. 1B) then Link 6
(e.g., FIG. 1C). FIG. 1C illustrates that in one instance virtual
machine 23 may be run on core 33 of a multi-core processor. System
100 is shown using virtual machine 23 to traverse Link 6. FIG. 1C
further illustrates virtual machine 23 encompassing a virtual
machine representation of the content (e.g., a music file) of the
real machine 130 post sequential activation of Link 1 then Link 6,
a virtual machine representation of the software (e.g., a
commercial database management system) of the real machine 130 post
sequential activation of Link 1 then Link 6, a virtual machine
representation of the hardware (e.g., a removable drive) of the
real machine 130 post sequential activation of Link 1 then Link 6,
and a virtual machine representation of the operating system (e.g.,
GNU, Berkeley Software Distribution) of the real machine 130 post
sequential activation of Link 1 then Link 6 (e.g., as such might
appear after activation of a link installed by a rootkit via
malware/spyware).
[0307] Those skilled in the art will appreciate that system 100 may
generate as many virtual machines as necessary to traverse
individual links of interest, that individual virtual machines may
run on a core of a multi-core processor comprising any number of
individual cores, and that the examples herein are used for sake of
clarity. Those skilled in the art will appreciate that examples
used herein are meant to be indicative of the fact that system 100
can run in whole or in part on proximate multi-core machines and/or
distal or multi-core machines, on distributed computing systems
(e.g., GRID or clustered), on local computing systems, or hosted
computing systems, etc.
[0308] FIG. 1D illustrates a representative view of an
implementation of real machine 130 (e.g., a desktop, notebook, or
other type computing system, and/or one or more peripheral
devices). FIG. 1D illustrates that implementations of real machine
130 may include all/part of computing device 132 and/or all/part of
one or one or more peripherals associated computing device 132. The
computing device 132 may be any device capable of processing one or
more programming instructions. For example, the computing device
132 may be a desktop computer, a laptop computer, a notebook
computer, a mobile phone, a personal digital assistant (PDA),
combinations thereof, and/or other suitable computing devices.
[0309] As noted, in some instances, real machine 130 may also
include at least a portion of one or more peripheral devices
connected/connectable (e.g., via wired, waveguide, or wireless
connections) to real machine 130. Peripheral devices may include
one or more printers 134, one or more fax machines 136, one or more
peripheral memory devices 138 (e.g., flash drive, memory stick),
one or more network adapters 139 (e.g., wired or wireless network
adapters), one or more music players 140, one or more cellular
telephones 142, one or more data acquisition devices 144 (e.g.,
robots) and/or one or more device actuators 146 (e.g., an hydraulic
arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
[0310] FIGS. 2-265 illustrate operational flows representing
example operations related to FIGS. 1A, 1B, 1C and 1D. In FIG. 2
and in following figures that include various examples of
operational flows, discussion and explanation may be provided with
respect to the above-described examples of FIGS. 1A, 1B, 1C, and 1D
and/or with respect to other examples and contexts. However, it
should be understood that the operational flows may be executed in
a number of other environments and contexts, and/or in modified
versions of FIGS. 1A, 1B, 1C, and 1D. Also, although the various
operational flows are presented in the sequence(s) illustrated, it
should be understood that the various operations may be performed
in other orders than those which are illustrated, or may be
performed concurrently.
[0311] Following are a series of flowcharts depicting
implementations. For ease of understanding, the flowcharts are
organized such that the initial flowcharts present implementations
via an example implementation and thereafter the following
flowcharts present alternate implementations and/or expansions of
the initial flowchart(s) as either sub-component operations or
additional component operations building on one or more
earlier-presented flowcharts. Those having skill in the art will
appreciate that the style of presentation utilized herein (e.g.,
beginning with a presentation of a flowchart(s) presenting an
example implementation and thereafter providing additions to and/or
further details in subsequent flowcharts) generally allows for a
rapid and easy understanding of the various process
implementations. In addition, those skilled in the art will further
appreciate that the style of presentation used herein also lends
itself well to modular and/or object-oriented program design
paradigms. Further, various operational steps may have common
reference numbering within the figures but it will be clear from
the context of the following descriptions that such reference
numbers are described as being specific to a given figure unless
such context dictates otherwise. For example, an operation 220 may
be a component operation of an operational flow 200C. In the
following descriptions and in the figures, such an operation 220
may be notated as "operation 220" of "operational flow 2000", as
"operation 2200", or in other similar manners.
Application Ser. No. 12/005,064 (1206-003-007A1-000000)
[0312] Referring to FIG. 2, after a start operation, the
operational flow 200 illustrates operation 210A, which illustrates
retrieving at least a portion of data from a data source (e.g. a
computer accessible from the internet). For example, FIG. 1A
illustrates a data retriever engine 102. Data retriever engine may
retrieve (e.g. download) data 110 (e.g. a web page) from a data
source such as a computer accessible from the internet.
Specifically, data 110 may be web content retrieved from the World
Wide Web via a computing device accessible from the internet. For
example, data retriever engine 102 may set a URL and add a query
string value to the URL. Data retriever engine 102 may then make a
request to the URL and scan the response received from the URL.
Data 110 may be a web site or web page containing one or more links
to additional web sites, such as shown, for example, in FIG. 1B
and/or FIG. 1C. Data 110 may in some instances be textual, a
two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content.
[0313] Then, operation 220A illustrates determining a content of
the data. FIG. 1A illustrates a data content determination engine
104. Data content determination engine 104 may determine the
content (e.g. text, audio, video, etc.) of the data 110 retrieved
from the data source by the data retriever engine 102. For example,
FIG. 1A illustrates that the data content determination engine 104
may include a database examination engine 112, a data transverser
engine 114, and a local data examination engine 116. A database
examination engine 112 may examine (e.g. scan) a database (e.g.
information retrieved from a storage server) of known data web
links) and compare the known data to the data 110 to determine data
content (e.g. data types such as text, image, audio and/or video
content). Additionally, database examination engine 112 may compare
a portion of data 110 (e.g. a data packet header) against a
database including a collection of data broken down into its
respective components (e.g. header, body). If the comparison yields
a reasonable match, the data type may be determined. Data content
determination may be transmitted from the database examination
engine 112 to the data content determination engine 104.
[0314] A data transverser engine 114 may traverse (e.g. parse) at
least a portion of the data (e.g. a portion of a web page) to
determine data content (e.g. an image or video) within the portion
of the data. Data traversal may occur in real time (e.g.
simultaneously as data is loading). Data content determination may
be transmitted from the data transverser engine 114 to the data
content determination engine 104.
[0315] A local data examination engine 116 may locally (e.g. on the
real machine 130) examine (e.g. analyze) at least a portion of the
data (e.g. data packets) to determine data content (e.g. an audio
file). For instance, local data examination engine 116 may view an
amount of html source code to locate markers signifying the type of
data content. Data content determination may be transmitted from
the local data examination engine 116 to the data content
determination engine 104. Data content determination engine 104 may
transmit a data content determination to the Effect of content
acceptability determination engine 106. The content of the data
[0316] 110 may be any textual, audible, or visual content loaded or
displayed after the data is retrieved by the data retriever engine
102. For instance, the content of the data 110 may be a web page
comprising text, sound, and/or an image, a link to a web page, a
video or any combination of text, sound, images, links to web
pages, and videos.
[0317] Then, operation 230A illustrates determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine having one or more end-user specified preferences.
FIG. 1A illustrates an Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive data and an associated data
content determination (e.g. data is an audio file) from data
content determination engine 104 post retrieval of data by data
retriever engine 102 and transfer of retrieved data to data content
determination engine 106. Effect of content acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to user
preferences regarding the operating system as reflected by user
preference database 120.
[0318] Then, operation 240A illustrates providing at least one data
display option based on the determining acceptability of the effect
of the content of the data. FIG. 1A illustrates a data provider
engine 108. Data provider engine 108 may be in communication with
Effect of content acceptability determination engine 106, which may
receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
post retrieval of data by data retriever engine 102 and transfer of
retrieved data to data content determination engine 104. Effect of
content acceptability determination engine 106 may transfer at
least effect of content acceptability determination to the data
provider engine 108 to provide at least one data display option. In
one example, data provider engine 108 (FIG. 1A) provides data via
placing the data on a visual display, where the content is such
that it meets one or more thresholds associated with the effect of
content acceptability determination. Provided data may be a list of
web links, a web page, or other data that either have been deemed
acceptable by effect of content acceptability determination engine
106 or that have been modified (e.g., obfuscated), such as by data
modification engine 122, such that the to-be-displayed content is
judged acceptable under user preferences. Provided data may be
modified via the data modification engine 122. For instance,
provided data may be obfuscated via the data obfuscation engine 124
(e.g., at least a portion of the displayed data may be blurred out
or disabled), or provided data may be anonymized via the data
anonymization engine 126 (e.g., at least a portion of the data may
be deleted entirely). Data content provider engine 108 (FIG. 1A)
may receive at least one display instruction (e.g. OK to display
links 1 and 2) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, a each of virtual
machines 11, 12, 13 may include one or more instruction generating
modules configured to provide an instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Such instruction may include an instruction to
the data content provider engine 108 to prevent the data content
provider engine 108 from displaying data that may configure a
hardware profile of real machine 130 counter to anti-viral settings
stored in the user preference database 120 (FIG. 1A), or an
instruction to the data content provider engine 108 to prevent the
data content provider engine 108 from displaying data that may
configure an operating system of real machine 130 counter to a
previous operating system of the real machine (130) (e.g. determine
if a rootkit has been installed).
[0319] FIG. 3 illustrates alternative embodiments of the example
operational flow 200A of FIG. 2. FIG. 3 illustrates example
embodiments where the operation 220 may include at least one
additional operation. Additional operations may include an
operation 302, an operation 304, and/or an operation 306.
[0320] Operation 302 illustrates examining a database of known data
for data information. Continuing the example above, data content
determination engine 104 (FIG. 1A) may receive data 110 retrieved
from a data source by the data retriever engine 102 and communicate
data 110 to the database examination engine 112. Database
examination engine 112 may be configured to examine a database of
data provided, for example, by a data provider service or a
database of data stored on a real machine 130. For instance, a
database may include a list of links viewed by a user or
pre-approved by a user based on one or more user-specified
preferences, such as links from a specific source of information
(e.g., the Roman Catholic Church). Database examination engine 112
may communicate the results of a database examination to the data
content determination engine 104.
[0321] Operation 304 illustrates traversing data in real time.
Continuing the example above, database transverser engine 114 (FIG.
1A) examines data received from the data content engine 104
following retrieval of data from the data retriever engine 102.
Data transverser engine 114 may be configured to scan the data 110
to determine a data content type (e.g. an image, a video or an
audio file). Database transverser engine 114 may communicate the
results of a data traversal to the data content determination
engine 104.
[0322] Operation 306 illustrates locally examining data. For
instance, continuing the example above, data content determination
engine 104 (FIG. 1A) may receive data 110 retrieved from a data
source (e.g. a computer accessible through the internet) by the
data retriever engine 102 and communicate data 110 to the local
data examination engine 116. The local examination engine 116 may
examine the data 110 on the real machine 130 at the location of the
real machine 130 (e.g. executed on a subsystem within the real
machine) to determine a data content type (e.g. a downloadable
software program). Local data examination engine 116 may
communicate the results of a local data examination to the data
content determination engine 104.
[0323] FIG. 4 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 4 illustrates example
embodiments where the operation 230 may include at least one
additional operation. Additional operations may include an
operation 402, an operation 404, an operation 406, an operation
408, and/or an operation 410.
[0324] Operation 402 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13. Each of virtual
machines 11, 12, and/or 13 may examine (e.g. scan) at least a
portion of data (e.g. an imbedded link on a webpage) to determine
if the data references additional data (e.g. one or more additional
links). Additional data may be a web page comprising text and/or an
image, a link to a web page, a video or any combination of text,
images, links to web pages, or videos. Virtual machines 11, 12, 13
may traverse additional data to determine an acceptability of an
effect of the data content. Effect of content acceptability
determination may be communicated to Effect of content
acceptability determination engine 106 (FIG. 1A) that may
communicate an effect of content acceptability determination to a
data provider engine 108 (FIG. 1A).
[0325] Further, operation 404 illustrates determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine having one or more end-user specified preferences by
determining whether data references additional data when loading.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. Any
of virtual machines
[0326] 12, 13 may examine the data in real time as it loads onto
the virtual machine 11,
[0327] 13. For instance, if a link to a webpage immediately (e.g.
as soon as the link is activated) references an additional link
(e.g. to redirect a user), a virtual machine 11, 12, 13 may
determine that such a reference to an additional link has been
made. Virtual machines 11, 12, 13 may determine whether data
references additional data at any time when the data is loading.
Effect of content acceptability determination engine 106 (FIG. 1A)
may communicate an effect of content acceptability determination to
a data provider engine 108 (FIG. 1A).
[0328] Operation 406 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine
[0329] 106 may transfer the data and associated data content
determination to the virtual machine module 118. Virtual machine
module 118 (FIG. 1A) may spawn at least one virtual machine 11, 12,
and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13. The data of an
additional link or links may be examined by at least one of virtual
machines 11, 12, 13 issuing a request to receive additional data
information from a remote computer (e.g. a computer at a
geographically distinct location).
[0330] Operation 408 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by examining a copy of
data from a location geographically distinct from a location of the
data. Continuing the example above, FIG. 1A illustrates the Effect
of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102 and
communication of retrieved data to data content determination
engine 104. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12, 13. Effect of
content acceptability determination engine 106 may transfer data
received from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13. The data of an
additional link or links may be examined by at least one of virtual
machines 11, 12, 13 issuing a request to a remote computer to
examine additional data information at the remote computer (e.g. a
computer at a geographically distinct location).
[0331] Further, operation 410 illustrates generating a substantial
duplicate of at least a part of a real machine at a location
geographically distinct from a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. For
instance, a virtual machine 11, 12, 13 of the real machine may be
located at a geographically distinct location such as a remote
server, or a remote system configured duplicate data from the real
machine 130 and to receive and examine real machine information
transferred to the remote server or remote system. System 100 may
include any number of communication modules (not shown) configured
to communicate over local or remote communication channels.
[0332] FIG. 5 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 5 illustrates example
embodiments where the operation 230 may include at least one
additional operation. Additional operations may include an
operation 502, an operation 504, an operation 506, and/or an
operation 508.
[0333] Operation 502 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of a substantial portion of a real machine
having one or more end-user specified preferences. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. For
instance, FIG. 1B illustrates virtual machines 11, 12, 14 including
a virtual machine representation of content of the real machine
130, software or the real machine 130, hardware of the real machine
130, and an operating system of the real machine 130. Virtual
machines 11, 12, 13 may include most or all of at least one of the
content of the real machine 130 (e.g. a substantial portion of the
text, image, audio, and video files of the real machine), software
of the real machine 130 (e.g. a substantial portion of any program
or suite of programs installed on the real machine), hardware of
the real machine 130 (a substantial portion of the circuitry
comprising the real machine), and/or an operating system of the
real machine 130 (e.g. a substantial portion of a Windows.RTM.
operating system installed on the real machine).
[0334] Operation 504 illustrates for determining an acceptability
of an effect of the content of the data at least in part via a
virtual machine representation of at least a portion of data on a
real machine having one or more end-user specified preferences.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 including a virtual
machine representation of content of the real machine 130, a
virtual machine representation of software of the real machine 130,
a virtual machine representation of hardware of the real machine
130, and/or a virtual machine representation of an operating system
of the real machine 130 post activation of link 1, link 2, and link
3 of data 110 (e.g., a Web page) resident on real machine 130.
These post activation states are examples of effects of the content
of data 110. As additional examples, virtual machines 11, 12, 13
may include at least a portion of at least one of the content of
the real machine 130 (e.g. the video files of a real machine),
software or the real machine 130 (e.g. iTunes), hardware of the
real machine 130 (e.g. a data processor), and/or an operating
system of the real machine 130 (e.g. a portion of
Netware.RTM.).
[0335] Operation 506 illustrates determining an acceptability of an
effect of data at least in part via a virtual machine
representation operating at a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B further illustrates virtual machines 11, 12, 13. In one
implementation, any of virtual machines 11, 12, 13 may be generated
on the real machine 130 (e.g. as a subsystem of real machine
130).
[0336] Operation 508 illustrates determining an acceptability of an
effect of data at least in part via a virtual machine
representation operating at a location geographically distinct from
a location of the data. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12, 13. FIG. 1B further illustrates virtual machines
11, 12, 13. In one implementation, any of virtual machines 11, 12,
13 may be generated on a remote server, remote operating system or
otherwise geographically distinct location with respect to the real
machine 130.
[0337] FIG. 6 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 6 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230 may include at least one additional
operation. Additional operations may include an operation 602, an
operation 604, an operation 606, and/or an operation 608.
[0338] Operation 602 illustrates determining an acceptability of an
effect of the content of the data on at least two virtual machine
representations of at least a part of a real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12, 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. FIG. 1B illustrates
virtual machines 11, 12, and 13. At least two of virtual machines
11, 12, 13 may include virtual machine representations of at least
a portion of software, hardware and an operating system of the real
machine 130.
[0339] Further, operation 604 illustrates determining an
acceptability of an effect of the content of the data on at least
two virtual machine representations of at least a part of a real
machine having one or more end-user specified preferences at least
one of the at least two virtual machine representations operating
on a separate operating system. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12, 13. For instance, a virtual machine 11, 12, 13
(FIG. 1A) may individually mimic one of Windows XP, Windows 2000
with SQL 2000 and SharePoint Server 2003, Windows 2003 with
Exchange 2003, an Apple operating system (e.g., MAC OS 9, OS X
Leopard), or Red Hat Linux with Apache. Further, each virtual
machine 11, 12, 13 may mimic a different operating system (e.g.,
virtual machine 11 may mimic Windows XP, virtual machine 12 may
mimic Windows 2000 and virtual machine 13 may mimic Red Hat Linux
and so on). Operating system may be any software configured to
manage the sharing of the resources of a computer, process system
data and user inputs, and respond to user inputs by allocating and
managing tasks and internal system resources. Operating system may
be, for example Microsoft Windows.RTM. 2000, XP, or Vista available
from Microsoft Corporation of Redmond, Wash., Mac OS X, Linux or
any other operating system.
[0340] Operation 606 illustrates determining an acceptability of an
effect of the content of the data on at least two virtual machine
representations of at least a part of a real machine having one or
more end-user specified preferences, at least one of the at least
two virtual machine representations operating on a separate core of
a system comprising at least two cores. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine
[0341] 106 further including a virtual machine module 118 and a
user preference database 120. Virtual machine module 118 includes
virtual machines 11, 12, 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. As illustrated in FIGS.
1B and 1C, each of virtual machine 11, virtual machine 12, virtual
machine 13, virtual machine 21, virtual machine 22, and virtual
machine 23 may operate on an individual core 11, 12, 13, 31, 32,
33, respectively, of a multi-core processor, or virtual machine 11
may run on one core and virtual machines 12, 13 may run on the
other core of a dual core processor such as an Intel.RTM. dual core
processor and so on. The multi-core processor may include a
plurality of processor cores packaged in one processor package. The
term core as used herein may refer, for example, to a single
processor of a multiprocessor system, or to a processor core of a
multi-core processor. Multi-core processor may be utilized as
portable computers such as laptop computers, personal digital
assistants, or desktop computers, or servers, or another form of
processor based system. Combinations of these types of platforms
may be present. The multi-core system may include a multi-core
processor, each core comprising a separate address space, and
having internal to that address space.
[0342] Operation 608, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location of the data. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12, 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. Each of virtual machines
11, 12, 13 may operate on a separate operating system at a location
of the data (e.g. executed on a subsystem, such as the virtual
machine module 118 (FIG. A) including a plurality of virtual
machines 11, 12, 13 (FIG. 1B) within the real machine 130).
[0343] FIG. 7 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 7 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230 may include at least one additional
operation. Additional operations may include an operation 702, an
operation 704, an operation 706, and/or an operation 708.
[0344] Operation 702 illustrates determining a state change of a
virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer the data
and associated data content determination to at least one of
virtual machines 11, 12, 13. A state change (e.g. a decrease in
memory) of virtual machine 11, 12, 13 (FIG. 1B) may be determined
by a component of virtual machine 11, 12, 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[0345] Operation 704 illustrates determining a state of a virtual
machine representation prior to loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12, 13.
Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. Virtual machine 11, 12,
13 may determine a state of at least one component (e.g. the
hardware) of the virtual machine prior to activation (e.g. before)
of a link. Virtual machine state may be representative of a state
for all or at least a portion of the components (e.g. content,
software, hardware, operating system) of the real machine 130
represented by the virtual machine 11, 12, and 13. For instance, a
virtual machine 11, 12, 13 may be determined to be free of viruses,
an amount of virtual machine memory may be measured, or a
processing speed of the virtual machine 11, 12, 13 may be
determined. Virtual machines 11, 12, 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[0346] Further, operation 706 illustrates determining a state of a
virtual machine after loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12, 13.
Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. Virtual machine 11, 12,
13 may determine a state of at least one component (e.g. the
hardware) of the virtual machine subsequent to (e.g. after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by the virtual machine
[0347] 12, 13 after at least a portion of the data has loaded. For
instance, a virtual machine 11, 12, 13 may be determined to contain
a virus, an amount of virtual machine memory may be measured, or a
processing speed of the virtual machine 11,
[0348] 13 may be determined. Virtual machine 11, 12, 13 may be
examined to determine, for example, if a virus or any other
undesired software is present on the machine after at least a
portion of the data has loaded by examining the virtual machine
representation of the operating system of the real machine 130
(FIG. 1B), or if information from the real machine 130 has been
transferred to an external location by examining the software of
the real machine 130.
[0349] Operation 708 illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data and associated data
content determination to at least one of virtual machines 11, 12,
13. An undesirable state change may be determined by examining the
changes to the virtual machine 11, 12, 13 and comparing the state
change of the virtual machine 11, 12, 13 to user preference
database information spawned on virtual machines 11, 12, 13 by a
transfer of user preference database information from the user
preference database 120 (FIG. 1A) to the virtual machine module 118
(FIG. 1A) which spawns a copy of at least a portion of the user
preference database 120 (FIG. 1A) onto virtual machines 11, 12, 13.
A state change may include any undesirable state changes such as a
decrease in memory or processing speed and/or the presence of a
virus or other undesirable software after at least a portion of the
data has loaded. Undesirable state changes may further include an
undesirable transfer of information located on the virtual machine
11, 12, 13 to an external location, an undesirable transfer of data
onto the virtual machine 11, 12, 13 from an external location after
at least a portion of the data has loaded on the virtual machine
11, 12, 13 that may result in an undesired change in the state of
content, software, hardware or an operating system of the real
machine 130 and/or an undesirable transfer of data onto the virtual
machine 11, 12, 13 where at least a portion of the transferred data
may be found objectionable when viewed by a user 10.
[0350] FIG. 8 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 8 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230 may include at least one additional
operation. Additional operations may include an operation 802, an
operation 804, an operation 806, an operation 808, and/or an
operation 810.
[0351] Operation 802 illustrates determining an acceptability of an
effect of the content of the data in response to at least one user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post retrieval of data by
data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, 13. An
undesirable state change may be determined by examining the changes
to the virtual machine 11, 12, 13 and comparing the state change of
the virtual machine 11, 12, 13 to user preference database
information spawned on virtual machines 11, 12, 13 by a transfer of
user preference database information from the user preference
database 120 (FIG. 1A) to the virtual machine module 118 (FIG. 1A)
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12, 13. User
preference database 120 may include at least one end-user specified
preference relating to at least one of content, software, hardware
and/or an operating system of a real machine 130. At least one of
virtual machines 11, 12, 13 may determine an acceptability of an
effect of the content of the data based on at least one user
setting contained in a user preference database at least a portion
of which may be spawned onto virtual machines 11, 12, 13 via
virtual machine module 118 (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a setting established by a user such as a political or
cultural preference setting). Further examples of user preferences
include specific religion or lifestyle preference, such as "return
only links relating to Roman Catholicism" or "return only links
relating to a vegan lifestyle" that may be stored in the real
machine 130. User-specific preference may also relate to user
information safety or computer safety, such as "do not display
links requesting information from my computer," or "do not display
links that transfer viruses onto my computer."
[0352] Operation 804 illustrates determining an acceptability of an
effect of the content of the data in response to a personal user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post retrieval of data by
data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, 13. User
preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12, 13. Virtual machines 11, 12, 13 may compare the data
received from the virtual machine module to a personal user setting
(e.g. "show only automobile related data") contained in user
preference database information spawned on virtual machines 11, 12,
13. User preference database 120 may include at least one personal
user setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130. Personal
user setting may be a setting input by a user that is personal to
the user, such as an information security level, a content filter
level, or a personal desirability setting such as "show only
non-religious data" or "show only automobile related data."
[0353] Further, operation 806 illustrates determining an
acceptability of an effect of the content of the data in response
to a peer user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module to a peer user
setting contained in user preference database information spawned
on virtual machines 11, 12, 13. User preference database 120 may
include at least one peer user setting relating to at least one of
content, software, hardware and/or an operating system of a real
machine 130. Peer user setting may be a setting input by a user
that is determined by a peer group, such as a peer group determined
information security level such as "display only 100 percent secure
websites", a peer group determined data filter level such as
"filter 100% of obscene data", or a peer group desirability setting
such as "show only classical music related data" or "show only
knitting related data."
[0354] Additionally, operation 808 illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a corporate
user setting contained in user preference database information
spawned on virtual machines 11, 12, 13. User preference database
120 may include at least one corporate user setting relating to at
least one of content, software, hardware and/or an operating system
of a real machine 130. Corporate user setting may be a setting
input by a corporation that is determined to the corporation, such
as a corporate desirability setting such as "show only real-estate
related data" or "show only agricultural related data."
[0355] Further, operation 810 illustrates determining an
acceptability of an effect of the content of the data in response
to a work safety user setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a work safety
user setting contained in user preference database information
spawned on virtual machines 11, 12, 13. User preference database
120 may include at least one work safety user setting relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. Thus, in one specific example, a
webpage or website data may be determined to be determined to be
displayable if the data satisfies a work safety user setting such
as a corporate information security level, corporate user setting,
or a corporate information content filter level corporate user
setting.
[0356] FIG. 9 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 9 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230 may include at least one additional
operation. Additional operations may include an operation 902, an
operation 904, an operation 906, an operation 908, an operation
910, and/or an operation 912.
[0357] Operation 902 illustrates determining an acceptability of an
effect of the content of the data in response to a desirability
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post retrieval of data by
data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, 13. User
preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12, 13. Virtual machines 11, 12, 13 may compare the data
received from the virtual machine module 118 to a desirability
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a desirability
setting established by a user such as a desire to view only
non-obscene material) contained in user preference database
information spawned on virtual machines 11, 12, 13. User preference
database 120 may include at least one desirability setting relating
to at least one of content, software, hardware and/or an operating
system of a real machine 130.
[0358] Operation 904 illustrates determining an acceptability of an
effect of the content of the data in response to a religious
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a religious
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a religious desirability setting established by a user such as a
desire to view only Hindu material) contained in user preference
database information spawned on virtual machines 11, 12, 13. A
religious desirability setting may be include any setting regarding
a major, minor, or other religion such as Christianity, Judaism,
Islam, Hinduism, and so on.
[0359] Operation 906 illustrates determining an acceptability of an
effect of the content of the data in response to a political
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a political
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a political desirability setting established by a user such as a
desire to view only Democratic Party material) contained in user
preference database information spawned on virtual machines 11, 12,
13. A political desirability setting may include any setting
regarding a political party or affiliation (e.g. Republican,
Democratic, Libertarian, Green Party, etc.).
[0360] Operation 908 illustrates determining an acceptability of an
effect of the content of the data in response to a cultural
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13.
[0361] Random access memories may include those such as those of
Sandisk Corporation and/or Samsung Electronics, Co., LTD), a data
bus, a hard disk (e.g., such as those of Seagate Technology, LLC),
a network adapter (e.g., wireless and/or wired LAN adapters such as
those of Linksys and/or CiscoTechnology, Inc.), printer, a
removable drive (e.g., flash drive), a cell phone, etc.
[0362] FIG. 1B also illustrates virtual machine 11 including a
virtual machine representation of an operating system (e.g., a
state of an operating system and/or network operating system) of
the real machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
e.g. Microsoft.RTM. Windows 2000, Unix, Linux, etc.) and/or a
network operating system (e.g., the Internet Operating System
available from Cisco Technology, Inc. Netware.RTM. available from
Novell, Inc., and/or Solaris available from Sun Microsystems,
Inc.).
[0363] FIG. 1B also illustrates that virtual machine 11 may run on
core 11 of a multi-core processor. In addition to the herein, those
skilled in the art will appreciate that the virtual machine
representations discussed herein are not limited to specific
examples described, but instead include any components of real
machine 130 as such might be understood in the art. Examples of the
foregoing would include firmware, logic associated with display
units, logic associated with robotics, application specific
integrated circuits, etc.
[0364] As noted, in some instances system 100 may traverse (e.g.
view) links of data 110 via one or virtual machine representations
of at least a part of real machine 130. Accordingly, FIG. 1B
illustrates virtual machine 12 encompassing a virtual machine
representation of real machine 130 (e.g., one or more states of one
or more components associated with real machine 130), post
activation of Link 2. FIG. 1B illustrates virtual machine 12 at
least partly running on core 12 of a multi-core processor. Virtual
machine module 118 (FIG. 1A) of Effect of content acceptability
determination engine 106 (FIG. 1A) may be illustrated to include
virtual machine 12.
[0365] FIG. 1B also illustrates virtual machine 12 may include a
virtual machine representation of content (e.g. a video) of real
machine 130 post activation of Link 2, a virtual machine
representation of software (e.g. Microsoft Office for Windows) of
machines 11, 12, 13. A theme related desirability setting may
include any theme related information, such as information relating
to cars, fashion, electronics, sports, hobbies, collector's items,
or any theme or category that may be of interest to a user.
[0366] Operation 912 illustrates determining an acceptability of an
effect of the content of the data in response to an age
appropriateness desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to an
age appropriateness desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on an age appropriateness desirability
setting established by a user such as a desire to view only
materials given a PG or lower rating as determined by the Motion
Picture of America Association film rating system) contained in
user preference database information spawned on virtual machines
11, 12, 13. An age appropriateness desirability setting may include
any age appropriate setting, such as a rating threshold or a
profanity threshold.
[0367] FIG. 10 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 10 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230 may include at least one additional
operation. Additional operations may include an operation 1002, an
operation 1004, an operation 1006, and/or an operation 1008.
[0368] Operation 1002 illustrates determining an acceptability of
an effect of the content of the data in response to at least one
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a privacy
related setting (e.g., does a website contain only images, text,
audio or visual data suitable for viewing by a user based on a
privacy related setting established by a user) contained in user
preference database information spawned on virtual machines 11, 12,
13. A privacy related setting may include any privacy related
settings (e.g., does a website contain only data that will not
request information from my computer or allow others to view
personal information saved on my computer).
[0369] Operation 1004 illustrates determining an acceptability of
an effect of the content of the data in response to a user specific
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a user
specific privacy related setting (e.g., will a website request
specific information about the user such as name, address,
telephone number) contained in user preference database information
spawned on virtual machines 11, 12, 13. A user specific privacy
related setting may include any user specific privacy related
settings (e.g., a setting relating to a user's biographical
information or financial information).
[0370] Further, operation 1006 illustrates determining an
acceptability of an effect of the content of the data in response
to a group privacy related setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to a
group privacy related setting (e.g., will a website request
information about an organization such as name, address, telephone
number) contained in user preference database information spawned
on virtual machines 11, 12, 13. A group privacy related setting may
include any group privacy related settings (e.g., a setting
relating to a group's membership). Group privacy related setting
may be any setting established by a group such as a work group
(e.g. employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g. members of family unit) privacy
related setting.
[0371] Further, operation 1008 illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate privacy related setting. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to a
corporate privacy related setting (e.g., will a website request
information about a corporation such as data stored on a real
machine belonging to the corporation) contained in user preference
database information spawned on virtual machines 11, 12, 13.
Corporate privacy related setting may be determined by a corporate
issued privacy manual, or other such document or mandate set forth
by officers of a corporation.
[0372] FIG. 11 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 11 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230 may include at least one additional
operation. Additional operations may include an operation 1102, an
operation 1104, an operation 1106, and/or an operation 1108.
[0373] Operation 1102 illustrates determining an acceptability of
an effect of the content of the data in response to a type of
transmitted user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to at least one
acceptable type of transmitted user information setting (e.g., do
not return links that will transmit my e-mail address, home address
or telephone number to an external location) contained in user
preference database information spawned on virtual machines 11, 12,
13. Acceptable type of transmitted user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be transmitted to a location external to the
real machine by selecting the link.
[0374] Further, operation 1104 illustrates determining an
acceptability of an effect of the content of the data in response
to a type of captured user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to at
least one acceptable type of captured user information setting
(e.g., do not return links that will capture my e-mail address,
home address or telephone number) contained in user preference
database information spawned on virtual machines 11, 12, 13.
Acceptable type of captured user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be captured by a machine located at a location
external to the real machine by selecting the link.
[0375] Further, operation 1106 illustrates determining an
acceptability of an effect of the content of the data in response
to a type of exposed user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to at
least one acceptable type of exposed user information setting
(e.g., do not return links that will expose personal financial
information stored on the real machine 130) contained in user
preference database information spawned on virtual machines 11, 12,
13.
[0376] Acceptable type of exposed user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be exposed to a machine located at a location
external to the real machine by selecting the link.
[0377] Operation 1108 illustrates determining an acceptability of
an effect of, the content of the data in response to visually
examining a data image. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. To visually examine a data image, a virtual machine 11, 12, 13
may include an image scanning module. Visually examining the data
image may include, for example, color analysis, pattern-matching,
pattern-recognition, or any other technique for recognizing a
particular image or type of image.
[0378] FIG. 12 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 12 illustrates example
embodiments where the determining an acceptability of the effect of
the data of the data operation 230 may include at least one
additional operation. Additional operations may include an
operation 1202.
[0379] Operation 1202, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location geographically distinct from a
location of the data. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. At least two virtual machines, for example
virtual machines 12, 13 may be virtual machines operating at
geographically distinct location such as a remote server, or a
remote system configured to receive and examine real machine
information transferred to the remote system and duplicate data
from the real machine 130. In some instances, each virtual machine
may be generated on one or more separate cores of a multi-core
processor.
[0380] FIG. 13 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 13 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1302, an operation
1304, an operation 1306, an operation 1308, and/or an operation
1310.
[0381] Operation 1302 illustrates providing a data display option
of displaying the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
video file) from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display the entire text of link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG.
[0382] 1A). Each of virtual machines 11, 12, 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate the
display instruction to the data content provider engine 108. Data
content provider engine 108 may then display the data. Displayed
data may be an unmodified web page of text, images and/or video, or
a web page including links to additional web pages and may be
displayed on a real machine display such as a computer screen.
[0383] Operation 1304 illustrates providing a data display option
of not displaying the data. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of not
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one do not display
instruction (e.g. Do not display the text of link 1) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12, 13 may
include one or more instruction generating modules configured to
provide a do not display instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the do not display instruction to the
data content provider engine 108. The data display option of not
displaying the data may include a message indicated why the data is
not being displayed, or may be, for example, a blank page displayed
on a display of the real machine.
[0384] Operation 1306 illustrates providing a data display option
of displaying a modified version of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a portion of
the data. For instance, data content provider engine 108 may
receive at least one modify data instruction (e.g. display only
lines 1-10 of the text of link 1) from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to provide a modify data
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate the
modify data instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine may transmit the modified data
to the data content provider engine 108. Data content provider
engine 108 may then display the modified version of the data.
Displayed data may be an modified web page of text, a modified
images and/or a modified video, or a modified web page including
links to additional web pages. For instance, a webpage or website
may be displaying, but any obscenities on the web page or website
may replaced by non-obscene word alternatives.
[0385] Further, operation 1308 illustrates providing a data display
option of obfuscating an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of obfuscating (e.g. blurring) a
portion of the data (e.g. obscene photos). For instance, data
content provider engine 108 may receive at least one obfuscate data
instruction (e.g. display only non-obscene portions of the image in
link 1) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12, 13 may include one or more instruction generating
modules configured to provide an obfuscate data instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the obfuscate data
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the obfuscate data
instruction to the data modification engine 122 which may transmit
the obfuscate data instruction to the data obfuscation engine 124.
Data obfuscation engine 124 may transmit the obfuscated data to the
data modification engine 122 for transmission to the data content
provider engine 108. Data content provider engine 108 may then
display the obfuscated version of the data. For example,
obfuscating logic may obfuscate restricted data or imagery within a
webpage or image. Obfuscation may include blurring or blocking of
the objectionable data portion.
[0386] Further, operation 1310 illustrates providing a data display
option of anonymizing an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of anonymizing (e.g. obscuring
source information) for a portion of the data (e.g. graphic
videos). For instance, data content provider engine 108 may receive
at least one anonymize data instruction (e.g. obscure source
information for portions of the video in link 1) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12, 13 may include one
or more instruction generating modules configured to provide an
anonymize data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the anonymize data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the anonymize data instruction to the data modification
engine 122 which may transmit the anonymize data instruction to the
data anonymization engine 126. Data anonymization engine 126 may
transmit the anonymized data to the data modification engine 122
for transmission to the data content provider engine 108. Data
content provider engine 108 may then display the anonymized version
of the data. Anonymized data may be data in which the original
identity information of the data is hidden, obscured, replaced,
and/or otherwise modified.
[0387] FIG. 14 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 14 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1402, an operation
1404, an operation 1406, and/or an operation 1408.
[0388] Operation 1402 illustrates providing a data display option
of removing, altering, or replacing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an audio file)
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of removing, altering or
replacing an objectionable data portion (e.g. replacing profanity
with innocuous language) for a portion of the data (e.g. explicit
lyrics). For instance, data content provider engine 108 may receive
at least one alter, remove or replace instruction (e.g. obscure
source information for portions of the video in link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the remove,
alter or replace data instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
anonymize data instruction to the data modification engine 122
which may then remove, alter or replace the data. Data modification
engine 122 may transmit the data containing removed, altered or
replaced portions to the data content provider engine 108. Data
content provider engine 108 may then display the data containing
removed, altered, or replaced portions. Thus, in one specific
example, a portion of a webpage produced by a search including data
relating to religions other than Catholicism may be removed from
the web page prior to display of the data on a real machine display
such as a computer screen.
[0389] Operation 1404 illustrates providing a data display option
of displaying a data portion consistent with at least one setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is text) from data
content determination engine 104 (FIG. 1A) post retrieval of data
by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g. OK to
display only text consistent with a corporate established setting)
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, 13. Effect of content acceptability determination engine
106 may communicate the display instruction to the data content
provider engine 108. If data needs to be modified to be consistent
with at least one setting, the data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108 (e.g., a setting such as recast all text to large, and
reformat a page consistent with the large text, such as might be
done for an individual having special vision needs). Data content
provider engine 108 may then display the data consistent with the
setting.
[0390] Further, operation 1406 illustrates providing a data display
option of displaying a data portion consistent with a privacy
related setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data does
not contain spyware) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one privacy related
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g. OK to display webpage) from
at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a privacy related setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one privacy related setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data consistent with the privacy
related setting. For instance, a portion of a returned webpage
including data requesting private user information such as a user's
social security number or e-mail address may be removed from the
web page prior to display of the data on a computer screen. Further
specific examples include a webpage or website data may be
determined to be displayable if the data satisfies a setting such
as a privacy related setting such as a setting relating to a user's
biographical information or financial information, a webpage or
website data may be determined to be displayable if the data
satisfies a group privacy related setting such as a work group
(e.g. employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g. members of family unit) privacy
related setting, or a webpage or website data may be determined to
be displayable if the data satisfies a privacy setting determined
by a corporation or other organization to maintain corporate or
organization privacy.
[0391] Further, operation 1408 illustrates providing a data display
option of displaying a data portion consistent with a user setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data does not contain
malware) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one user setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12, 13 may include one
or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one user setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data consistent with the user
setting. Thus, a webpage or website data may be determined to be
displayable if the data satisfies a user setting when the virtual
machine 11, 12, 13 compares the data to the user setting. For
instance, a portion of a webpage produced by a search including
non-English text may be removed from the web page prior to display
of the data on a computer screen. Further, in one specific example,
a webpage or website data may be determined to be displayable if
the data satisfies a peer user setting, or a webpage or website
data may be determined to be displayable if the data satisfies, for
instance, a corporate user setting.
[0392] FIG. 15 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 15 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1502, and/or an
operation 1504.
[0393] Operation 1502 illustrates providing a data display option
of displaying a data portion consistent with a desirability
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a desirability
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one desirability
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data portion
consistent with the desirability setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with a Christian desirability
setting such as "display only Christianity related data." In other
examples, a webpage or website data may be determined to be
displayable if the data satisfies a desirability setting, a webpage
or website data may be determined to be displayable if the data
satisfies a religious desirability setting such as a Christian,
Jewish, and/or Muslim, based religious desirability setting, or may
be based on any other major, minor or alternative religious
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a political desirability
setting such as a Republican, Democratic, Libertarian or Green
Party political desirability setting, a webpage or website data may
be determined to be displayable if the data satisfies a cultural
desirability setting such as a religious, ethnic, regional, or
heritage based cultural desirability setting or any other cultural
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a theme related
desirability setting such as boating or card games, or a webpage or
website data may be determined to be displayable if the data
satisfies an age appropriateness desirability setting such as a
setting based on the Motion Picture of America Association film
rating system.
[0394] Further, operation 1504 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
social networking site) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one workplace established
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g. do not display data) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace established setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace established setting,
the data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data portion consistent with the
workplace established setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a workplace appropriateness desirability
setting such as "display only non-obscene data."
[0395] FIG. 16 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 16 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1602, an operation
1604, and/or an operation 1606.
[0396] Operation 1602 illustrates providing a data display option
of displaying a data portion consistent with a safety setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an image) from
data content determination engine 104 (FIG. 1A) post retrieval of
data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
(e.g. OK to display image) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one safety setting, the data content
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with child
safety setting such as "display only non-violent data," or "display
only ethnic and gender neutral data."
[0397] Further, operation 1604 illustrates providing a data display
option of displaying a data portion consistent with a public safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a desirability
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one public safety
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data content provider engine 108 may then
display the data portion consistent with the public safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with
public safety setting such as "display only non-confidential
data."
[0398] Further, operation 1606 illustrates providing a data display
option of displaying a data portion consistent with a home safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one home safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a home safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If data needs to be modified to be
consistent with at least one home safety setting, the data content
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
content provider engine 108 may then display the data portion
consistent with the home safety setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with home safety setting such as
"okay to display private or confidential data."
[0399] FIG. 17 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 17 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1702, and/or an
operation 1704.
[0400] Operation 1702 illustrates providing a data display option
of displaying a data portion consistent with a workplace safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace safety setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace safety setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a workplace
safety setting such as "display only non-personal data."
[0401] Further, operation 1704 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one child safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a child safety setting stored in a copy of
the user preference database 120
[0402] (FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect
of content acceptability determination engine 106 may communicate
the display instruction to the data content provider engine 108. If
data needs to be modified to be consistent with at least one child
safety setting, the data content provider engine 108 may transmit
the modify data instruction to the data modification engine 122 for
modification of the data. Data content provider engine 108 may then
display the data portion consistent with the child safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with a
child safety setting such as "display only non-violent data."
[0403] FIG. 18 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 18 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1802, an operation
1804, an operation 1806, and/or an operation 1808.
[0404] Operation 1802 illustrates redirecting to alternative data a
user may be redirected to alternative data. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data.
[0405] Operation 1804 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a privacy related
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a privacy related setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a privacy related setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a privacy related setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a privacy related setting may include displaying a
different webpage including only information consistent with a
privacy related setting such as "display only links that do not
request e-mail addresses." Privacy related setting may be any
privacy related setting described above and may include any
additional privacy related settings.
[0406] Further, operation 1806 illustrates displaying alternative
data consistent with a customized user setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a customized user
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a customized user setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a customized user setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a customized user setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a customized user setting may include displaying a
different webpage including only information consistent with a
customized user setting such as "display only links containing
French text." Thus, in one specific example, a webpage or website
data may be determined to be displayable if the data satisfies a
customized user setting when the virtual machine 11, 12, 13
compares the data to the customized user setting.
[0407] Further, operation 1808 illustrates displaying alternative
data consistent with a desirability setting. Continuing the example
above, data provider engine 108 (FIG.
[0408] 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of redirecting to alternative data
consistent with a desirability setting (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a desirability setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a desirability setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a desirability setting may include displaying a
different webpage including only information consistent with a
desirability setting such as "display only links containing
information relating to art." Desirability setting may be any
desirability setting described above and may include any additional
desirability settings.
[0409] FIG. 19 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 19 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 1902, and/or an
operation 1904.
[0410] Operation 1902 illustrates displaying alternative data
consistent with a workplace established setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace
established setting (e.g. another website). For instance, data
content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12, 13 may include one or more instruction generating
modules configured to provide a redirect instruction to the Effect
of content acceptability determination engine 106 after a
comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a workplace established setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace established setting.
The data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a workplace established setting may include
displaying a different webpage including only information
consistent with a workplace established setting such as "do not
display links to social networking websites."
[0411] Operation 1904 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a user history
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user history setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a user history setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. For instance, displayed alternative data may be
consistent with a user history such as having viewed only music
related data and pages.
[0412] FIG. 20 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 20 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 2002, an operation
2004, and/or an operation 2006.
[0413] Operation 2002 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine
[0414] 106 may transfer effect of content acceptability
determination to the data provider engine 108 to provide the data
display option of redirecting to alternative data consistent with a
safety setting (e.g. another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a safety setting instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the redirect data instruction to the data redirection
engine 128 for redirection to alternative data consistent with a
safety setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a safety setting may
include displaying a different webpage including only information
consistent with a safety setting such as "do not display links
requesting credit card information."
[0415] Operation 2004 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction
[0416] generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the redirect to alternative data consistent with a
workplace safety setting instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a workplace safety
setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a workplace safety
setting may include displaying a different webpage including only
information consistent with a workplace safety setting such as "do
not display links requesting information on this computer."
[0417] Operation 2006 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a child safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a child safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a child safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
child safety setting may include displaying a different webpage
including only information consistent with a child safety setting
such as "do not display links containing trailers for rated `R`
movies."
[0418] FIG. 21 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 21 illustrates example
embodiments where the providing at least one data display option
operation 240 may include at least one additional operation.
Additional operations may include an operation 2102, an operation
2104, an operation 2106, and/or an operation 2108.
[0419] Operation 2102 illustrates displaying alternative data
consistent with a public safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a public safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a public safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a public safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a public safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a public safety setting may include displaying a
different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[0420] Operation 2104 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a home safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a home safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a home safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
home safety setting may include displaying a different webpage
including only information consistent with a home safety setting
such as "do not display links requesting address information."
[0421] Operation 2106 illustrates automatically redirecting to
alternative data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of redirecting to alternative data
(e.g. another website) consistent with a user preference. For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with the user preference instruction to
the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with the user preference. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then automatically
(e.g. prior to alerting a user) display the alternative data. For
instance, a real machine 130 may be automatically redirected to an
acceptable web link, or a page of acceptable data.
[0422] Further, operation 2108 illustrates providing a list of
selectable alternative data options. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of providing a list of
selectable alternative data options (e.g. a list of alternative
websites) consistent with a user preference. For instance, data
content provider engine 108 may receive at least one provide
selectable alternatives instruction from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to transmit a provide
selectable alternatives instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the provide selectable alternatives
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the provide selectable
alternatives instruction to the data redirection engine 128 to
provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data content provider engine 108.
Data content provider engine 108 may then display the list of
selectable alternatives. For instance, the list of selectable
alternative data options may include a list of acceptable web links
or a selectable list of web pages. Selectable web links and web
pages may include a thumbnail image of the first page of the web
link or of the web page.
[0423] FIG. 22 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 22 illustrates example
embodiments where the providing at least one data display option
operation 230 may include at least one additional operation.
Additional operations may include an operation 2202, an operation
2204, an operation 2206, and/or an operation 2208.
[0424] At the operation 2202, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2, and/or link 3 actually been traversed on real machine 130). FIG.
1B further illustrates virtual machines 11, 12, 13 including a
virtual machine representation of content of the real machine 130
post activation of Link 1, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
email, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation may include determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine include determining whether or not a video or image
has been loaded onto, for example, the virtual machine 11 after
loading at least a portion of the data contained in Link 1.
[0425] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine on a
virtual machine representation of at least a portion of a real
machine generated by, for example, virtual machine 11. FIG. 1C
illustrates a partial follow-on operational view of real machine
130 (e.g., a desktop, notebook, or other type computing system) in
which at least a portion of system 100 (FIG. 1A) has been
implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0426] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6 post traversal of
Link 1. Accordingly, FIG. 1C illustrates system 100 generating
virtual machine representations of real machine 130, used to
traverse Links 4, 5, and 6, in the context of virtual machines 21,
22, and 23, respectively. Those skilled in the art will thus
appreciate that, in the example shown in FIG. 1C, system 100 is
creating second-order virtual machine representations to
prospectively investigate the effects on the states of various
components of real machine 130 via sequential traversals of links.
That is, the virtual machine representations of real machine 130
encompassed in virtual machine 21, virtual machine 22, and virtual
machine 23 of FIG. 1C are generated by system 100 based on the
first-order virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0427] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of content
(e.g., a movie, web page, music file, etc.) of the real machine 130
post sequential activation of Link 1 then Link 4, virtual machine
22 including a virtual machine representation of content (e.g. a
graphical image, a text file, an email, etc.) of the real machine
130 post (e.g., subsequent to) sequential activation of Link 1 then
Link 5, and virtual machine 23 encompassing a virtual machine
representation of the content (e.g. a music file) of the real
machine 130 post sequential activation of Link 1 then Link 6. A
determination of an acceptability of an effect of the content of
data on the content of the real machine made on virtual machine 21
may include determining whether or not an audio file has been
loaded onto virtual machine 21. Virtual machine 21 may communicate
a determination of an acceptability of an effect of the content of
data determination made on a virtual machine 21 which may be at
least a portion of content of the real machine to virtual machine
11, which may communicate the acceptability of an effect of the
content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0428] At the operation 2204, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2, and/or link 3 actually been traversed on real machine 130). FIG.
1B illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software) of the real
machine 130 post (e.g. subsequent to) activation of Link 1.
Examples of such software might include a commercial word
processing program or suite of programs (e.g. Microsoft.RTM. Office
for Windows), an open source Web browser (e.g., Mozilla's
Firefox.RTM. Browser), an AJAX mash up (e.g., an executing
JavaScript.TM. and/or data retrieved by same via an XML-like
scheme), or a commercial database management system (e.g., one or
more of Oracle Corporation's various products), a commercial
anti-malware/spyware programs (e.g., such as those of Symantec
Corporation or McAfee, Inc.), etc. An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation may include determining
an acceptability of an effect of the content of the data at least
in part via a virtual machine
[0429] representation of at least a portion of the software of the
real machine include determining whether or not an unauthorized
program or suite of programs (e.g. music downloading software) has
been loaded, for example, onto virtual machine 12 after loading at
least a portion of the data contained in Link 2.
[0430] determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine on a
virtual machine representation of at least a portion of the
software of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0431] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0432] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
software (e.g.) of the real machine 130 post sequential activation
of Link 1 then Link 4, virtual machine 22 including a virtual
machine representation of software (e.g. an AJAX mashup) of the
real machine 130 post sequential activation of Link 1 then Link 5,
and a virtual machine representation of the software (e.g. a
commercial database management system) of the real machine 130 post
sequential activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the software
of the real machine made on virtual machine 21 may include
determining whether or not malware or grayware has been loaded onto
virtual machine 21. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
software of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0433] At the operation 2206, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the hardware of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2 or link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of hardware (e.g. a state of the hardware) of the
real machine 130 post activation of Link 1. Examples of such
hardware might include all or part of a chipset (e.g., data
processor and/or graphics processor chipsets such as those of Intel
Corporation and/or NvidiaCorporation), a memory chip (e.g., flash
memory and/or random access memories such as those of Sandisk
Corporation and/or Samsung Electronics, Co., LTD), a data bus, a
hard disk (e.g., such as those of Seagate Technology, LLC), a
network adapter (e.g., wireless and/or wired LAN adapters such as
those of Linksys and/or CiscoTechnology, Inc.), printer, a
removable drive (e.g., flash drive), a cell phone, etc. An example
of determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a portion of the hardware of the real machine include
determining whether a network adapter on, for example, virtual
machine 12 has been disabled after loading at least a portion of
the data contained in Link 2.
[0434] determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine on a
virtual machine representation of at least a portion of the
hardware of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0435] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0436] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
hardware (e.g. the circuitry or processor of the real machine) of
the real machine 130 post sequential activation of Link 1 then Link
4, a virtual machine representation of hardware (e.g. a network
adapter) of the real machine 130 post sequential activation of Link
1 then Link 5, and a virtual machine representation of the hardware
(e.g. a removable drive) of the real machine 130 post sequential
activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the hardware
of the real machine made on virtual machine 21 may include
determining whether a decrease in processor speed of virtual
machine 21 has occurred. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
hardware of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0437] At the operation 2208, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the operating
system of the real machine. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12, 13. Effect of
content acceptability determination engine 106 may transfer data
received from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2, and/or link 3 actually been traversed on real machine 130). FIG.
1B also illustrates virtual machine 11 including a virtual machine
representation of an operating system (e.g., a state of an
operating system and/or network operating system) of the real
machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
e.g. Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or a
network operating system (e.g., the Internet Operating System
available from Cisco Technology, Inc. Netware.RTM. available from
Novell, Inc., and/or Solaris available from Sun Microsystems,
Inc.). An example of determining an acceptability of an effect of
the content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of an operating system of the
real machine include determining whether a portion of the operating
system (e.g. Microsoft Vista) on for example, virtual machine 12
has been disabled after loading at least a portion of the data
contained in Link 2.
[0438] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the operating system of the real machine
may also include determining an acceptability of an effect of the
content of the data at least in part via a
[0439] virtual machine representation includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a portion of
the operating system of the real machine on a virtual machine
representation of at least a portion of the operating system of a
real machine generated by, for example, virtual machine 11. FIG. 1C
illustrates a partial follow-on operational view of real machine
130 (e.g., a desktop, notebook, or other type computing system) in
which at least a portion of system 100 (FIG. 1A) has been
implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0440] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0441] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
operating system (e.g. Linux) of the real machine 130 post
sequential activation of Link 1 then Link 4, a virtual machine
representation of an operating system (e.g. Mac OS/X) of the real
machine 130 post sequential activation of Link 1 then Link 5, and a
virtual machine representation of the operating system (e.g. GNU,
Berkeley Software Distribution) of the real machine 130 post
sequential activation of Link 1 then Link 6 (e.g., as such might
appear after activation of a link installed by a rootkit via
malware/spyware). A determination of an acceptability of an effect
of the content of data on the operating system of the real machine
made on virtual machine 21 may include determining whether or not a
rootkit has been installed onto virtual machine 21. Virtual machine
21 may communicate a determination of acceptability of an effect of
the content of data on a virtual machine representation of at least
a portion of operating system of the real machine made on virtual
machine 21 to virtual machine 11, which may communicate the
acceptability of an effect of the content of data determination to
the virtual machine module 118 (FIG. 1A) for communication to the
Effect of content acceptability determination engine 106 (FIG.
1A).
[0442] FIG. 23 illustrates alternative embodiments of the example
operational flow 200 of FIG. 2. FIG. 23 illustrates example
embodiments where the providing at least one data display option
operation 230 may include at least one additional operation.
Additional operations may include an operation 2302, an operation
2304, and/or an operation 2306.
[0443] At the operation 2302, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least a part of a computing device. FIG.
1D illustrates real machine 130 including at least a part of a
computing device 132. The computing device 132 may be any device
capable of processing one or more programming instructions. For
example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[0444] At the operation 2304, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
may spawn virtual machines 11, 12, 13 that may be virtual machine
representations of at least a part of real machine 130. Real
machine 130 may include at least one peripheral device. For
instance, FIG. 1D illustrates real machine 130 including at least
one peripheral device 134-146. FIG. 1D illustrates a representative
view of an implementation of real machine 130 (e.g., a desktop,
notebook, or other type computing system, and/or one or more
peripheral devices) in which all/part of system 100 may be
implemented. FIG. 1D illustrates that implementations of real
machine 130 may include all/part of computing device 132 and/or
all/part of one or one or more peripherals associated computing
device 132.
[0445] At the operation 2306, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a
[0446] part of a real machine having one or more end-user specified
preferences includes determining an acceptability of an effect of
the content of the data at least in part via a virtual machine
representation of at least a part of a real machine including at
least one peripheral device that is at least one of a printer, a
fax machine, a peripheral memory device, a network adapter, a music
player, a cellular telephone, a data acquisition device, or a
device actuator. Continuing the example above, FIG. 1A illustrates
the Effect of content acceptability determination engine 106.
Effect of content acceptability determination engine 106 may
receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 may spawn virtual machines 11, 12, 13
that may be virtual machine representations of at least a part of
real machine 130. Real machine 130 may include at least one
peripheral device. For instance, FIG. 1D illustrates a real machine
may also include at least a portion of one or more peripheral
devices connected/connectable (e.g., via wired, waveguide, or
wireless connections) to real machine 130. Peripheral devices may
include one or more printers 134, one or more fax machines 136, one
or more peripheral memory devices 138 (e.g., flash drive, memory
stick), one or more network adapters 139 (e.g., wired or wireless
network adapters), one or more music players 140, one or more
cellular telephones 142, one or more data acquisition devices 144
(e.g. robots) and/or one or more device actuators 146 (e.g., an
hydraulic arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
Application Ser. No. 12/154,423 (1206-003-007A1-000001)
[0447] FIG. 24 illustrates an operational flow 200A representing
example operations related to FIGS. 1A, 1B, 1C and 1D. In FIG. 2
and in following figures that include various examples of
operational flows, discussion and explanation may be provided with
respect to the above-described examples of FIGS. 1A, 1B, 1C, and 1D
and/or with respect to other examples and contexts. However, it
should be understood that the operational flows may be executed in
a number of other environments and contexts, and/or in modified
versions of FIGS. 1A, 1B, IC, and 1D. Also, although the various
operational flows are presented in the sequence(s) illustrated, it
should be understood that the various operations may be performed
in other orders than those which are illustrated, or may be
performed concurrently.
[0448] After a start operation, the operational flow 200A
illustrates operation 210, which illustrates retrieving at least a
portion of data from a data source (e.g. a computer accessible from
the internet). For example, FIG. 1A illustrates a data retriever
engine 102. Data retriever engine may retrieve (e.g. download) data
110 (e.g. a web page) from a data source such as a computer
accessible from the internet. Specifically, data 110 may be web
content retrieved from the World Wide Web via a computing device
accessible from the interne. For example, data retriever engine 102
may set a URL and add a query string value to the URL. Data
retriever engine 102 may then make a request to the URL and scan
the response received from the URL. Data 110 may be a web site or
web page containing one or more links to additional web sites, such
as shown, for example, in FIG. 1B and/or FIG. 1C. Data 110 may in
some instances be textual, a two-dimensional or three-dimensional
image, audible, or video representations, which in some instances
may entail programming code such as html, JavaScript, C, C++, or
any other programming code capable of producing text, visual
images, audio content, video content or any combination of text,
visual images, audible content and video content.
[0449] Then, operation 220A illustrates determining a content of
the data. FIG. 1A illustrates a data content determination engine
104. Data content determination engine 104 may determine the
content (e.g. text, audio, video, etc.) of the data 110 retrieved
from the data source by the data retriever engine 102. For example,
FIG. 1A illustrates that the data content determination engine 104
may include a database examination engine 112, a data transverser
engine 114, and a local data examination engine 116. A database
examination engine 112 may examine (e.g. scan) a database (e.g.
information retrieved from a storage server) of known data (e.g.
web links) and compare the known data to the data 110 to determine
data content (e.g. data types such as text, image, audio and/or
video content). Additionally, database examination engine 112 may
compare a portion of data 110 (e.g. a data packet header) against a
database including a collection of data broken down into its
respective components (e.g. header, body). If the comparison yields
a reasonable match, the data type may be determined. Data content
determination may be transmitted from the database examination
engine 112 to the data content determination engine 104.
[0450] A data transverser engine 114 may traverse (e.g. parse) at
least a portion of the data (e.g. a portion of a web page) to
determine data content (e.g. an image or video) within the portion
of the data. Data traversal may occur in real time (e.g.
simultaneously as data is loading). Data content determination may
be transmitted from the data transverser engine 114 to the data
content determination engine 104.
[0451] A local data examination engine 116 may locally (e.g. on the
real machine 130) examine (e.g. analyze) at least a portion of the
data (e.g. data packets) to determine data content (e.g. an audio
file). For instance, local data examination engine 116 may view an
amount of html source code to locate markers signifying the type of
data content. Data content determination may be transmitted from
the local data examination engine 116 to the data content
determination engine 104. Data content determination engine 104 may
transmit a data content determination to the Effect of content
acceptability determination engine 106. The content of the data 110
may be any textual, audible, or visual content loaded or displayed
after the data is retrieved by the data retriever engine 102. For
instance, the content of the data 110 may be a web page comprising
text, sound, and/or an image, a link to a web page, a video or any
combination of text, sound, images, links to web pages, and
videos.
[0452] Then, operation 230A illustrates determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine having one or more end-user specified preferences.
FIG. 1A illustrates an Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive data and an associated data
content determination (e.g. data is an audio file) from data
content determination engine 104 post retrieval of data by data
retriever engine 102 and transfer of retrieved data to data content
determination engine 106. Effect of content acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to user
preferences regarding the operating system as reflected by user
preference database 120.
[0453] Then, operation 240A illustrates providing at least one data
display option based on the determining acceptability of the effect
of the content of the data. FIG. 11-A illustrates a data provider
engine 108. Data provider engine 108 may be in communication with
Effect of content acceptability determination engine 106, which may
receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
post retrieval of data by data retriever engine 102 and transfer of
retrieved data to data content determination engine 104. Effect of
content acceptability determination engine 106 may transfer at
least effect of content acceptability determination to the data
provider engine 108 to provide at least one data display option. In
one example, data provider engine 108 (FIG. 1A) provides data via
placing the data on a visual display, where the content is such
that it meets one or more thresholds associated with the effect of
content acceptability determination. Provided data may be a list of
web links, a web page, or other data that either have been deemed
acceptable by effect of content acceptability determination engine
106 or that have been modified (e.g., obfuscated), such as by data
modification engine 122, such that the to-be-displayed content is
judged acceptable under user preferences. Provided data may be
modified via the data modification engine 122. For instance,
provided data may be obfuscated via the data obfuscation engine 124
(e.g., at least a portion of the displayed data may be blurred out
or disabled), or provided data may be anonymized via the data
anonymization engine 126 (e.g., at least a portion of the data may
be deleted entirely). Data content provider engine 108 (FIG. 1A)
may receive at least one display instruction (e.g. OK to display
links 1 and 2) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, at least a portion
of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Such instruction
may include an instruction to the data content provider engine 108
to prevent the data content provider engine 108 from displaying
data that may configure a hardware profile of real machine 130
counter to anti-viral settings stored in the user preference
database 120 (FIG. 1A), or an instruction to the data content
provider engine 108 to prevent the data content provider engine 108
from displaying data that may configure an operating system of real
machine 130 counter to a previous operating system of the real
machine (130) (e.g. determine if a rootkit has been installed).
[0454] FIG. 25 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 25 illustrates example
embodiments where the operation 220A may include at least one
additional operation. Additional operations may include an
operation 302A, an operation 304A, and/or an operation 306A.
[0455] Operation 302A illustrates examining a database of known
data for data information. Continuing the example above, data
content determination engine 104 (FIG. 1A) may receive data 110
retrieved from a data source by the data retriever engine 102 and
communicate data 110 to the database examination engine 112.
Database examination engine 112 may be configured to examine a
database of data provided, for example, by a data provider service
or a database of data stored on a real machine 130. For instance, a
database may include a list of links viewed by a user or
pre-approved by a user based on one or more user-specified
preferences, such as links from a specific source of information
(e.g., the Roman Catholic Church). Database examination engine 112
may communicate the results of a database examination to the data
content determination engine 104.
[0456] Operation 304A illustrates traversing data in real time.
Continuing the example above, database transverser engine 114 (FIG.
1A) examines data received from the data content engine 104
following retrieval of data from the data retriever engine 102.
Data transverser engine 114 may be configured to scan the data 110
to determine a data content type (e.g. an image, a video or an
audio file). Database transverser engine 114 may communicate the
results of a data traversal to the data content determination
engine 104.
[0457] Operation 306A illustrates locally examining data. For
instance, continuing the example above, data content determination
engine 104 (FIG. 1A) may receive data 110 retrieved from a data
source (e.g. a computer accessible through the internet) by the
data retriever engine 102 and communicate data 110 to the local
data examination engine 116. The local examination engine 116 may
examine the data 110 on the real machine 130 at the location of the
real machine 130 (e.g. executed on a subsystem within the real
machine) to determine a data content type (e.g. a downloadable
software program). Local data examination engine 116 may
communicate the results of a local data examination to the data
content determination engine 104.
[0458] FIG. 26 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 26 illustrates example
embodiments where the operation 230A may include at least one
additional operation. Additional operations may include an
operation 402A, an operation 404A, an operation 406A, an operation
408A, and/or an operation 410.
[0459] Operation 402A illustrates determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13. Each of
virtual machines 11, 12, and/or 13 may examine (e.g. scan) at least
a portion of data (e.g. an imbedded link on a webpage) to determine
if the data references additional data (e.g. one or more additional
links). Additional data may be a web page comprising text and/or an
image, a link to a web page, a video or any combination of text,
images, links to web pages, or videos. Virtual machines 11, 12
and/or 13 may traverse additional data to determine an
acceptability of an effect of the data content. Effect of content
acceptability determination may be communicated to Effect of
content acceptability determination engine 106 (FIG. 1A) that may
communicate an effect of content acceptability determination to a
data provider engine 108 (FIG. 1A).
[0460] Further, operation 404A illustrates determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine having one or more end-user specified preferences by
determining whether data references additional data when loading.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
Any of virtual machines 11, 12 and/or 13 may examine the data in
real time as it loads onto the virtual machine 11, 12 and/or 13.
For instance, if a link to a webpage immediately (e.g. as soon as
the link is activated) references an additional link (e.g. to
redirect a user), a virtual machine 11, 12 and/or 13 may determine
that such a reference to an additional link has been made. Virtual
machines 11, 12 and/or 13 may determine whether data references
additional data at any time when the data is loading. Effect of
content acceptability determination engine 106 (FIG. 1A) may
communicate an effect of content acceptability determination to a
data provider engine 108 (FIG. 1A).
[0461] Operation 406A illustrates determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13. The data of
an additional link or links may be examined by at least one of
virtual machines 11, 12 and/or 13 issuing a request to receive
additional data information from a remote computer (e.g. a computer
at a geographically distinct location).
[0462] Operation 408A illustrates determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by examining a copy of
data from a location geographically distinct from a location of the
data. Continuing the example above, FIG. 1A illustrates the Effect
of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102 and
communication of retrieved data to data content determination
engine 104. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12 and/or 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. FIG. 1B illustrates virtual machines 11,
12 and/or 13. The data of an additional link or links may be
examined by at least one of virtual machines 11, 12 and/or 13
issuing a request to a remote computer to examine additional data
information at the remote computer (e.g. a computer at a
geographically distinct location).
[0463] Further, operation 410A illustrates generating a substantial
duplicate of at least a part of a real machine at a location
geographically distinct from a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
For instance, a virtual machine 11, 12 and/or 13 of the real
machine may be located at a geographically distinct location such
as a remote server, or a remote system configured duplicate data
from the real machine 130 and to receive and examine real machine
information transferred to the remote server or remote system.
System 100 may include any number of communication modules (not
shown) configured to communicate over local or remote communication
channels.
[0464] FIG. 27 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 27 illustrates example
embodiments where the operation 230A may include at least one
additional operation. Additional operations may include an
operation 502A, an operation 504A, an operation 506A, and/or an
operation 508A.
[0465] Operation 502A illustrates determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of a substantial portion of a real machine
having one or more end-user specified preferences. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
For instance, FIG. 1B illustrates virtual machines 11, 12, 14
including a virtual machine representation of content of the real
machine 130, software or the real machine 130, hardware of the real
machine 130, and an operating system of the real machine 130.
Virtual machines 11, 12 and/or 13 may include most or all of at
least one of the content of the real machine 130 (e.g. a
substantial portion of the text, image, audio, and video files of
the real machine), software of the real machine 130 (e.g. a
substantial portion of any program or suite of programs installed
on the real machine), hardware of the real machine 130 (a
substantial portion of the circuitry comprising the real machine),
and/or an operating system of the real machine 130 (e.g. a
substantial portion of a Windows.RTM. operating system installed on
the real machine).
[0466] Operation 504A illustrates for determining an acceptability
of an effect of the content of the data at least in part via a
virtual machine representation of at least a portion of data on a
real machine having one or more end-user specified preferences.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 including a
virtual machine representation of content of the real machine 130,
a virtual machine representation of software of the real machine
130, a virtual machine representation of hardware of the real
machine 130, and/or a virtual machine representation of an
operating system of the real machine 130 post activation of link 1,
link 2, and link 3 of data 110 (e.g., a Web page) resident on real
machine 130. These post activation states are examples of effects
of the content of data 110. As additional examples, virtual
machines 11, 12 and/or 13 may include at least a portion of at
least one of the content of the real machine 130 (e.g. the video
files of a real machine), software or the real machine 130 (e.g.
iTunes), hardware of the real machine 130 (e.g. a data processor),
and/or an operating system of the real machine 130 (e.g. a portion
of Netware.RTM.).
[0467] Operation 506A illustrates determining an acceptability of
an effect of data at least in part via a virtual machine
representation operating at a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B further illustrates virtual machines 11, 12 and/or 13. In
one implementation, any of virtual machines 11, 12 and/or 13 may be
generated on the real machine 130 (e.g. as a subsystem of real
machine 130).
[0468] Operation 508A illustrates determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation operating at a location geographically
distinct from a location of the data. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. FIG. 1B further
illustrates virtual machines 11, 12 and/or 13. In one
implementation, any of virtual machines 11, 12 and/or 13 may be
generated on a remote server, remote operating system or otherwise
geographically distinct location with respect to the real machine
130.
[0469] FIG. 28 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 28 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230A may include at least one additional
operation. Additional operations may include an operation 602A, an
operation 604A, an operation 606A, and/or an operation 608A.
[0470] Operation 602A illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. FIG. 1B illustrates
virtual machines 11, 12, and 13. At least two of virtual machines
11, 12 and/or 13 may include virtual machine representations of at
least a portion of software, hardware and an operating system of
the real machine 130.
[0471] Further, operation 604A illustrates determining an
acceptability of an effect of the content of the data on at least
two virtual machine representations of at least a part of a real
machine having one or more end-user specified preferences at least
one of the at least two virtual machine representations operating
on a separate operating system. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. For instance, a virtual machine 11, 12
and/or 13 (FIG. 1A) may individually mimic one of Windows XP,
Windows 2000 with SQL 2000 and SharePoint Server 2003, Windows 2003
with Exchange 2003, an Apple operating system (e.g., MAC OS 9, OS X
Leopard), or Red Hat Linux with Apache. Further, each virtual
machine 11, 12 and/or 13 may mimic a different operating system
(e.g., virtual machine 11 may mimic Windows XP, virtual machine 12
may mimic Windows 2000 and virtual machine 13 may mimic Red Hat
Linux and so on). Operating system may be any software configured
to manage the sharing of the resources of a computer, process
system data and user inputs, and respond to user inputs by
allocating and managing tasks and internal system resources.
Operating system may be, for example Microsoft Windows.RTM. 2000,
XP, or Vista available from Microsoft Corporation of Redmond,
Wash., Mac OS X, Linux or any other operating system.
[0472] Operation 606A illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
core of a system comprising at least two cores. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
As illustrated in FIGS. 1B and 1C, each of virtual machine 11,
virtual machine 12, virtual machine 13, virtual machine 21, virtual
machine 22, and virtual machine 23 may operate on an individual
core 11, 12 and/or 13, 31, 32, 33, respectively, of a multi-core
processor, or virtual machine 11 may run on one core and virtual
machines 12 and/or 13 may run on the other core of a dual core
processor such as an Intel.RTM. dual core processor and so on. The
multi-core processor may include a plurality of processor cores
packaged in one processor package. The term core as used herein may
refer, for example, to a single processor of a multiprocessor
system, or to a processor core of a multi-core processor.
Multi-core processor may be utilized as portable computers such as
laptop computers, personal digital assistants, or desktop
computers, or servers, or another form of processor based system.
Combinations of these types of platforms may be present. The
multi-core system may include a multi-core processor, each core
comprising a separate address space, and having internal to that
address space.
[0473] Operation 608A, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location of the data. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. Each of virtual
machines 11, 12 and/or 13 may operate on a separate operating
system at a location of the data (e.g. executed on a subsystem,
such as the virtual machine module 118 (FIG. A) including a
plurality of virtual machines 11, 12 and/or 13 (FIG. 1B) within the
real machine 130).
[0474] FIG. 29 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 29 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230A may include at least one additional
operation. Additional operations may include an operation 702A, an
operation 704A, an operation 706A, and/or an operation 708A.
[0475] Operation 702A illustrates determining a state change of a
virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. A state change (e.g. a decrease
in memory) of virtual machine 11, 12 and/or 13 (FIG. 1B) may be
determined by a component of virtual machine 11, 12 and/or 13
measuring a characteristic of the virtual machine representation of
the content, software, hardware or operating system of the real
machine 130 before and after the at least a portion of data has
loaded. For instance, a state change may be measured after a search
result containing a plurality of web links has loaded and at least
one web link has been activated.
[0476] Operation 704A illustrates determining a state of a virtual
machine representation prior to loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12 and/or
13. Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. Virtual machine 11,
12 and/or 13 may determine a state of at least one component (e.g.
the hardware) of the virtual machine prior to activation (e.g.
before) of a link. Virtual machine state may be representative of a
state for all or at least a portion of the components (e.g.
content, software, hardware, operating system) of the real machine
130 represented by the virtual machine 11, 12 and/or 13. For
instance, a virtual machine 11, 12 and/or 13 may be determined to
be free of viruses, an amount of virtual machine memory may be
measured, or a processing speed of the virtual machine 11, 12
and/or 13 may be determined. Virtual machines 11, 12 and/or 13 may
contain a diagnostic application configured to analyze virtual
machine performance and contents.
[0477] Further, operation 706A illustrates determining a state of a
virtual machine after loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12 and/or
13. Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. Virtual machine 11,
12 and/or 13 may determine a state of at least one component (e.g.
the hardware) of the virtual machine subsequent to (e.g. after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by the virtual machine 11, 12 and/or 13 after at least
a portion of the data has loaded. For instance, a virtual machine
11, 12 and/or 13 may be determined to contain a virus, an amount of
virtual machine memory may be measured, or a processing speed of
the virtual machine 11, 12 and/or 13 may be determined. Virtual
machine 11, 12 and/or 13 may be examined to determine, for example,
if a virus or any other undesired software is present on the
machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[0478] Operation 708A illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. An undesirable state change may be
determined by examining the changes to the virtual machine 11, 12
and/or 13 and comparing the state change of the virtual machine 11,
12 and/or 13 to user preference database information spawned on
virtual machines 11, 12 and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. 1A)
onto virtual machines 11, 12 and/or 13. A state change may include
any undesirable state changes such as a decrease in memory or
processing speed and/or the presence of a virus or other
undesirable software after at least a portion of the data has
loaded. Undesirable state changes may further include an
undesirable transfer of information located on the virtual machine
11, 12 and/or 13 to an external location, an undesirable transfer
of data onto the virtual machine 11, 12 and/or 13 from an external
location after at least a portion of the data has loaded on the
virtual machine 11, 12 and/or 13 that may result in an undesired
change in the state of content, software, hardware or an operating
system of the real machine 130 and/or an undesirable transfer of
data onto the virtual machine 11, 12 and/or 13 where at least a
portion of the transferred data may be found objectionable when
viewed by a user 10.
[0479] FIG. 30 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 30 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230A may include at least one additional
operation. Additional operations may include an operation 802A, an
operation 804A, an operation 806A, an operation 808A, and/or an
operation 810A.
[0480] Operation 802A illustrates determining an acceptability of
an effect of the content of the data in response to at least one
user setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12 and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
An undesirable state change may be determined by examining the
changes to the virtual machine 11, 12 and/or 13 and comparing the
state change of the virtual machine 11, 12 and/or 13 to user
preference database information spawned on virtual machines 11, 12
and/or 13 by a transfer of user preference database information
from the user preference database 120 (FIG. 1A) to the virtual
machine module 118 (FIG. 1A) which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12 and/or 13. User preference database 120 may include
at least one end-user specified preference relating to at least one
of content, software, hardware and/or an operating system of a real
machine 130. At least one of virtual machines 11, 12 and/or 13 may
determine an acceptability of an effect of the content of the data
based on at least one user setting contained in a user preference
database at least a portion of which may be spawned onto virtual
machines 11, 12 and/or 13 via virtual machine module 118 (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a setting established by a
user such as a political or cultural preference setting). Further
examples of user preferences include specific religion or lifestyle
preference, such as "return only links relating to Roman
Catholicism" or "return only links relating to a vegan lifestyle"
that may be stored in the real machine 130. User-specific
preference may also relate to user information safety or computer
safety, such as "do not display links requesting information from
my computer," or "do not display links that transfer viruses onto
my computer."
[0481] Operation 804A illustrates determining an acceptability of
an effect of the content of the data in response to a personal user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12 and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
User preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12 and/or 13. Virtual machines 11, 12 and/or 13 may compare the
data received from the virtual machine module to a personal user
setting (e.g. "show only automobile related data") contained in
user preference database information spawned on virtual machines
11, 12 and/or 13. User preference database 120 may include at least
one personal user setting relating to at least one of content,
software, hardware and/or an operating system of a real machine
130. Personal user setting may be a setting input by a user that is
personal to the user, such as an information security level, a
content filter level, or a personal desirability setting such as
"show only non-religious data" or "show only automobile related
data."
[0482] Further, operation 806A illustrates determining an
acceptability of an effect of the content of the data in response
to a peer user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module to
a peer user setting contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. User
preference database 120 may include at least one peer user setting
relating to at least one of content, software, hardware and/or an
operating system of a real machine 130. Peer user setting may be a
setting input by a user that is determined by a peer group, such as
a peer group determined information security level such as "display
only 100 percent secure websites", a peer group determined data
filter level such as "filter 100% of obscene data", or a peer group
desirability setting such as "show only classical music related
data" or "show only knitting related data."
[0483] Additionally, operation 808A illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a corporate user setting contained in user preference
database information spawned on virtual machines 11, 12 and/or 13.
User preference database 120 may include at least one corporate
user setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130.
Corporate user setting may be a setting input by a corporation that
is determined to the corporation, such as a corporate desirability
setting such as "show only real-estate related data" or "show only
agricultural related data."
[0484] Further, operation 810A illustrates determining an
acceptability of an effect of the content of the data in response
to a work safety user setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a work safety user setting contained in user preference
database information spawned on virtual machines 11, 12 and/or 13.
User preference database 120 may include at least one work safety
user setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130. Thus, in
one specific example, a webpage or website data may be determined
to be determined to be displayable if the data satisfies a work
safety user setting such as a corporate information security level,
corporate user setting, or a corporate information content filter
level corporate user setting.
[0485] FIG. 31 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 31 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230A may include at least one additional
operation. Additional operations may include an operation 902A, an
operation 904A, an operation 906A, an operation 908A, an operation
910A, and/or an operation 912A.
[0486] Operation 902A illustrates determining an acceptability of
an effect of the content of the data in response to a desirability
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12 and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
User preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12 and/or 13. Virtual machines 11, 12 and/or 13 may compare the
data received from the virtual machine module 118 to a desirability
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a desirability
setting established by a user such as a desire to view only
non-obscene material) contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. User
preference database 120 may include at least one desirability
setting relating to at least one of content, software, hardware
and/or an operating system of a real machine 130.
[0487] Operation 904A illustrates determining an acceptability of
an effect of the content of the data in response to a religious
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a religious desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a religious desirability setting
established by a user such as a desire to view only Hindu material)
contained in user preference database information spawned on
virtual machines 11, 12 and/or 13. A religious desirability setting
may be include any setting regarding a major, minor, or other
religion such as Christianity, Judaism, Islam, Hinduism, and so
on.
[0488] Operation 906A illustrates determining an acceptability of
an effect of the content of the data in response to a political
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a political desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a political desirability setting
established by a user such as a desire to view only Democratic
Party material) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. A political
desirability setting may include any setting regarding a political
party or affiliation (e.g. Republican, Democratic, Libertarian,
Green Party, etc.).
[0489] Operation 908A illustrates determining an acceptability of
an effect of the content of the data in response to a cultural
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a cultural desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a cultural desirability setting
established by a user such as a desire to view only materials
regarding early Mayan civilization) contained in user preference
database information spawned on virtual machines 11, 12 and/or 13.
A cultural desirability setting may include any culturally related
information such as a religious, ethnic, regional, or heritage
based cultural desirability setting or any other cultural
desirability setting.
[0490] Operation 910A illustrates determining an acceptability of
an effect of the content of the data in response to a theme related
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a theme related desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a theme related desirability setting
established by a user such as a desire to view only materials
regarding collectible stamps) contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. A theme
related desirability setting may include any theme related
information, such as information relating to cars, fashion,
electronics, sports, hobbies, collector's items, or any theme or
category that may be of interest to a user.
[0491] Operation 912A illustrates determining an acceptability of
an effect of the content of the data in response to an age
appropriateness desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. I A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to an age appropriateness
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
an age appropriateness desirability setting established by a user
such as a desire to view only materials given a PG or lower rating
as determined by the Motion Picture of America Association film
rating system) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. An age
appropriateness desirability setting may include any age
appropriate setting, such as a rating threshold or a profanity
threshold.
[0492] FIG. 32 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 32 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230A may include at least one additional
operation. Additional operations may include an operation 1002A, an
operation 1004A, an operation 1006A, and/or an operation 1008A.
[0493] Operation 1002A illustrates determining an acceptability of
an effect of the content of the data in response to at least one
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a privacy related setting (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a privacy related setting established by a user) contained
in user preference database information spawned on virtual machines
11, 12 and/or 13. A privacy related setting may include any privacy
related settings (e.g., does a website contain only data that will
not request information from my computer or allow others to view
personal information saved on my computer).
[0494] Operation 1004A illustrates determining an acceptability of
an effect of the content of the data in response to a user specific
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a user specific privacy related setting (e.g., will a
website request specific information about the user such as name,
address, telephone number) contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. A user
specific privacy related setting may include any user specific
privacy related settings (e.g., a setting relating to a user's
biographical information or financial information).
[0495] Further, operation 1006A illustrates determining an
acceptability of an effect of the content of the data in response
to a group privacy related setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to a group privacy related
setting (e.g., will a website request information about an
organization such as name, address, telephone number) contained in
user preference database information spawned on virtual machines
11, 12 and/or 13. A group privacy related setting may include any
group privacy related settings (e.g., a setting relating to a
group's membership). Group privacy related setting may be any
setting established by a group such as a work group (e.g. employees
of a company), a peer group (e.g., members of a book club), or a
family group (e.g. members of family unit) privacy related
setting.
[0496] Further, operation 1008A illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate privacy related setting. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to a corporate privacy related
setting (e.g., will a website request information about a
corporation such as data stored on a real machine belonging to the
corporation) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. Corporate privacy
related setting may be determined by a corporate issued privacy
manual, or other such document or mandate set forth by officers of
a corporation.
[0497] FIG. 33 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 33 illustrates example
embodiments where the determining an acceptability of the effect of
the data operation 230A may include at least one additional
operation. Additional operations may include an operation 1102A, an
operation 1104A, an operation 1106A, and/or an operation 1108A.
[0498] Operation 1102A illustrates determining an acceptability of
an effect of the content of the data in response to a type of
transmitted user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to at least one acceptable type of transmitted user information
setting (e.g., do not return links that will transmit my e-mail
address, home address or telephone number to an external location)
contained in user preference database information spawned on
virtual machines 11, 12 and/or 13. Acceptable type of transmitted
user information setting may be determined by a user 10 (FIG. 1B).
For instance, acceptability of the effect of the data may be
determined in response to whether or not private user information,
such as credit card numbers, bank accounts, personal identification
information or any other personal user information may be
transmitted to a location external to the real machine by selecting
the link.
[0499] Further, operation 1104A illustrates determining an
acceptability of an effect of the content of the data in response
to a type of captured user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to at least one acceptable type
of captured user information setting (e.g., do not return links
that will capture my e-mail address, home address or telephone
number) contained in user preference database information spawned
on virtual machines 11, 12 and/or 13. Acceptable type of captured
user information setting may be determined by a user 10 (FIG. 1B).
For instance, acceptability of the effect of the data may be
determined in response to whether or not private user information,
such as credit card numbers, bank accounts, personal identification
information or any other personal user information may be captured
by a machine located at a location external to the real machine by
selecting the link.
[0500] Further, operation 1106A illustrates determining an
acceptability of an effect of the content of the data in response
to a type of exposed user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to at least one acceptable type
of exposed user information setting (e.g., do not return links that
will expose personal financial information stored on the real
machine 130) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. Acceptable type of
exposed user information setting may be determined by a user 10
(FIG. 1B). For instance, acceptability of the effect of the data
may be determined in response to whether or not private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information
may be exposed to a machine located at a location external to the
real machine by selecting the link.
[0501] Operation 1108A illustrates determining an acceptability of
an effect of the content of the data in response to visually
examining a data image. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. To visually examine a data image, a virtual machine
11, 12 and/or 13 may include an image scanning module. Visually
examining the data image may include, for example, color analysis,
pattern-matching, pattern-recognition, or any other technique for
recognizing a particular image or type of image.
[0502] FIG. 34 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 34 illustrates example
embodiments where the determining an acceptability of the effect of
the data of the data operation 230A may include at least one
additional operation. Additional operations may include an
operation 1202A.
[0503] Operation 1202A, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location geographically distinct from a
location of the data. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. At least two virtual machines,
for example virtual machines 12 and/or 13 may be virtual machines
operating at geographically distinct location such as a remote
server, or a remote system configured to receive and examine real
machine information transferred to the remote system and duplicate
data from the real machine 130. In some instances, each virtual
machine may be generated on one or more separate cores of a
multi-core processor.
[0504] FIG. 36 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 36 illustrates example
embodiments where the providing at least one data display option
operation 240A may include at least one additional operation.
Additional operations may include an operation 1302A, an operation
1304A, an operation 1306A, an operation 1308A, and/or an operation
1310A.
[0505] Operation 1302A illustrates providing a data display option
of displaying the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
video file) from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display the entire text of link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. Data content provider engine
108 may then display the data. Displayed data may be an unmodified
web page of text, images and/or video, or a web page including
links to additional web pages and may be displayed on a real
machine display such as a computer screen.
[0506] Operation 1304A illustrates providing a data display option
of not displaying the data. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of not
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one do not display
instruction (e.g. Do not display the text of link 1) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may
include one or more instruction generating modules configured to
provide a do not display instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the do not display
instruction to the data content provider engine 108. The data
display option of not displaying the data may include a message
indicated why the data is not being displayed, or may be, for
example, a blank page displayed on a display of the real
machine.
[0507] Operation 1306A illustrates providing a data display option
of displaying a modified version of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a portion of
the data. For instance, data content provider engine 108 may
receive at least one modify data instruction (e.g. display only
lines 1-10 of the text of link 1) from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a modify data
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the modify data instruction to the data content provider engine
108. The data content provider engine 108 may transmit the modify
data instruction to the data modification engine 122 for
modification of the data. Data modification engine may transmit the
modified data to the data content provider engine 108. Data content
provider engine 108 may then display the modified version of the
data. Displayed data may be a modified web page of text, a modified
image and/or a modified video, or a modified web page including
links to additional web pages. For instance, a webpage or website
may be displaying, but any obscenities on the web page or website
may replaced by non-obscene word alternatives.
[0508] Further, operation 1308A illustrates providing a data
display option of obfuscating an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is a video file)
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of obfuscating (e.g. blurring) a
portion of the data (e.g. obscene photos). For instance, data
content provider engine 108 may receive at least one obfuscate data
instruction (e.g. display only non-obscene portions of the image in
link 1) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12 and/or 13 may include one or more instruction
generating modules configured to provide an obfuscate data
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the obfuscate data instruction to the data content provider engine
108. The data content provider engine 108 may transmit the
obfuscate data instruction to the data modification engine 122
which may transmit the obfuscate data instruction to the data
obfuscation engine 124. Data obfuscation engine 124 may transmit
the obfuscated data to the data modification engine 122 for
transmission to the data content provider engine 108. Data content
provider engine 108 may then display the obfuscated version of the
data. For example, obfuscating logic may obfuscate restricted data
or imagery within a webpage or image. Obfuscation may include
blurring or blocking of the objectionable data portion.
[0509] Further, operation 1310A illustrates providing a data
display option of anonymizing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is a video file)
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of anonymizing (e.g. obscuring
source information) for a portion of the data (e.g. graphic
videos). For instance, data content provider engine 108 may receive
at least one anonymize data instruction (e.g. obscure source
information for portions of the video in link 1) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may
include one or more instruction generating modules configured to
provide an anonymize data instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the anonymize data
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the anonymize data
instruction to the data modification engine 122 which may transmit
the anonymize data instruction to the data anonymization engine
126. Data anonymization engine 126 may transmit the anonymized data
to the data modification engine 122 for transmission to the data
content provider engine 108. Data content provider engine 108 may
then display the anonymized version of the data. Anonymized data
may be data in which the original identity information of the data
is hidden, obscured, replaced, and/or otherwise modified.
[0510] FIG. 36 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 36 illustrates example
embodiments where the providing at least one data display option
operation 2400A may include at least one additional operation.
Additional operations may include an operation 1402A, an operation
1404A, an operation 1406A, and/or an operation 1408A.
[0511] Operation 1402A illustrates providing a data display option
of removing, altering, or replacing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an audio file)
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of removing, altering or
replacing an objectionable data portion (e.g. replacing profanity
with innocuous language) for a portion of the data (e.g. explicit
lyrics). For instance, data content provider engine 108 may receive
at least one alter, remove or replace instruction (e.g. obscure
source information for portions of the video in link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may communicate the remove,
alter or replace data instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
anonymize data instruction to the data modification engine 122
which may then remove, alter or replace the data. Data modification
engine 122 may transmit the data containing removed, altered or
replaced portions to the data content provider engine 108. Data
content provider engine 108 may then display the data containing
removed, altered, or replaced portions. Thus, in one specific
example, a portion of a webpage produced by a search including data
relating to religions other than Catholicism may be removed from
the web page prior to display of the data on a real machine display
such as a computer screen.
[0512] Operation 1404A illustrates providing a data display option
of displaying a data portion consistent with at least one setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is text) from data
content determination engine 104 (FIG. 1A) post retrieval of data
by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g. OK to
display only text consistent with a corporate established setting)
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12 and/or 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If data needs to be modified to be
consistent with at least one setting, the data content provider
engine 108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108 (e.g., a setting such as recast all
text to large, and reformat a page consistent with the large text,
such as might be done for an individual having special vision
needs). Data content provider engine 108 may then display the data
consistent with the setting.
[0513] Further, operation 1406A illustrates providing a data
display option of displaying a data portion consistent with a
privacy related setting. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination (e.g.
data does not contain spyware) from data content determination
engine 104 (FIG. 1A) post retrieval of data by data retriever
engine 102 (FIG. 1A). Effect of content acceptability determination
engine 106 may transfer effect of content acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
privacy related setting. For instance, data content provider engine
108 may receive at least one display instruction (e.g. OK to
display webpage) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12 and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a privacy related setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one privacy related
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data consistent
with the privacy related setting. For instance, a portion of a
returned webpage including data requesting private user information
such as a user's social security number or e-mail address may be
removed from the web page prior to display of the data on a
computer screen. Further specific examples include a webpage or
website data may be determined to be displayable if the data
satisfies a setting such as a privacy related setting such as a
setting relating to a user's biographical information or financial
information, a webpage or website data may be determined to be
displayable if the data satisfies a group privacy related setting
such as a work group (e.g. employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g. members of
family unit) privacy related setting, or a webpage or website data
may be determined to be displayable if the data satisfies a privacy
setting determined by a corporation or other organization to
maintain corporate or organization privacy.
[0514] Further, operation 1408A illustrates providing a data
display option of displaying a data portion consistent with a user
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data does
not contain malware) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one user setting. For
instance, data content provider engine 108 may receive at least one
display instruction (e.g. OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one user setting, the data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108. Data content provider engine 108 may then display the
data consistent with the user setting. Thus, a webpage or website
data may be determined to be displayable if the data satisfies a
user setting when the virtual machine 11, 12 and/or 13 compares the
data to the user setting. For instance, a portion of a webpage
produced by a search including non-English text may be removed from
the web page prior to display of the data on a computer screen.
Further, in one specific example, a webpage or website data may be
determined to be displayable if the data satisfies a peer user
setting, or a webpage or website data may be determined to be
displayable if the data satisfies, for instance, a corporate user
setting.
[0515] FIG. 37 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 37 illustrates example
embodiments where the providing at least one data display option
operation 240A may include at least one additional operation.
Additional operations may include an operation 1502A, and/or an
operation 1504A.
[0516] Operation 1502A illustrates providing a data display option
of displaying a data portion consistent with a desirability
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12 and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
desirability, setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one desirability setting, the data content provider engine
108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the desirability
setting. For instance, the data display option may be displaying on
a display of a real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[0517] Further, operation 1504A illustrates providing a data
display option of displaying a data portion consistent with a
workplace established setting. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination (e.g.
data is a social networking site) from data content determination
engine 104 (FIG. 1A) post retrieval of data by data retriever
engine 102 (FIG. 1A). Effect of content acceptability determination
engine 106 may transfer effect of content acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
workplace established setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g. do
not display data) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12 and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12 and/or 13. Effect of
content acceptability determination engine 106 may communicate the
display instruction to the data content provider engine 108. If
data needs to be modified to be consistent with at least one
workplace established setting, the data content provider engine 108
may transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108. Data content provider engine 108 may then display the
data portion consistent with the workplace established setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a workplace
appropriateness desirability setting such as "display only
non-obscene data."
[0518] FIG. 38 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 38 illustrates example
embodiments where the providing at least one data display option
operation 240A may include at least one additional operation.
Additional operations may include an operation 1602A, an operation
1604A, and/or an operation 1606A.
[0519] Operation 1602A illustrates providing a data display option
of displaying a data portion consistent with a safety setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an image) from
data content determination engine 104 (FIG. 1A) post retrieval of
data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
(e.g. OK to display image) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one safety setting,
the data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data portion consistent with the
safety setting. For instance, the data display option may be
displaying on a display of a real machine only a data portion
consistent with child safety setting such as "display only
non-violent data," or "display only ethnic and gender neutral
data."
[0520] Further, operation 1604A illustrates providing a data
display option of displaying a data portion consistent with a
public safety setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12 and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
desirability setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one public safety setting, the data content provider engine
108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the public safety setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with public safety setting such as "display only
non-confidential data."
[0521] Further, operation 1606A illustrates providing a data
display option of displaying a data portion consistent with a home
safety setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one home safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a home safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one home safety setting, the data
content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the home safety setting. For instance,
the data display option may be displaying on a display of a real
machine only a data portion consistent with home safety setting
such as "okay to display private or confidential data."
[0522] FIG. 39 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24. FIG. 39 illustrates example
embodiments where the providing at least one data display option
operation 240A may include at least one additional operation.
Additional operations may include an operation 1702A, and/or an
operation 1704A.
[0523] Operation 1702A illustrates providing a data display option
of displaying a data portion consistent with a workplace safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace safety setting stored in a copy
of the user preference database 120 (FIG. I A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace safety setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a workplace
safety setting such as "display only non-personal data."
[0524] Further, operation 1704A illustrates providing a data
display option of displaying a data portion consistent with a child
safety setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one child safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a child safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one child safety setting, the data
content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the child safety setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a child safety
setting such as "display only non-violent data."
[0525] FIG. 40 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1802, an operation 1804, an operation 1806, and/or an
operation 1808.
[0526] Operation 1802 illustrates redirecting to alternative data a
user may be redirected to alternative data. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the redirect instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
[0527] Operation 1804 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a privacy related
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a privacy related setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a privacy related setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a privacy related setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a privacy related setting may include displaying a
different webpage including only information consistent with a
privacy related setting such as "display only links that do not
request e-mail addresses." Privacy related setting may be any
privacy related setting described above and may include any
additional privacy related settings.
[0528] Further, operation 1806 illustrates displaying alternative
data consistent with a customized user setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a customized user
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a customized user setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a customized user setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a customized user setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a customized user setting may include displaying a
different webpage including only information consistent with a
customized user setting such as "display only links containing
French text." Thus, in one specific example, a webpage or website
data may be determined to be displayable if the data satisfies a
customized user setting when the virtual machine 11, 12 and/or 13
compares the data to the customized user setting.
[0529] Further, operation 1808 illustrates displaying alternative
data consistent with a desirability setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a desirability
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a desirability setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a desirability setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a desirability setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
desirability setting may include displaying a different webpage
including only information consistent with a desirability setting
such as "display only links containing information relating to
art." Desirability setting may be any desirability setting
described above and may include any additional desirability
settings.
[0530] FIG. 41 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1902, and/or an operation 1904.
[0531] Operation 1902 illustrates displaying alternative data
consistent with a workplace established setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace
established setting (e.g. another website). For instance, data
content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12 and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12 and/or 13. Effect of
content acceptability determination engine 106 may communicate the
redirect to alternative data consistent with a workplace
established setting instruction to the data content provider engine
108. The data content provider engine 108 may transmit the redirect
data instruction to the data redirection engine 128 for redirection
to alternative data consistent with a workplace established
setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a workplace established
setting may include displaying a different webpage including only
information consistent with a workplace established setting such as
"do not display links to social networking websites."
[0532] Operation 1904 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a user history
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user history setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a user history setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. For instance, displayed alternative data may be
consistent with a user history such as having viewed only music
related data and pages.
[0533] FIG. 42 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 2002, an operation 2004, and/or an operation 2006.
[0534] Operation 2002 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of redirecting to alternative
data consistent with a safety setting (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the redirect to alternative data consistent with a safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a safety setting may include displaying a different
webpage including only information consistent with a safety setting
such as "do not display links requesting credit card
information."
[0535] Operation 2004 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a workplace safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a workplace safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace safety setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a workplace safety setting may include displaying a
different webpage including only information consistent with a
workplace safety setting such as "do not display links requesting
information on this computer."
[0536] Operation 2006 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a child safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a child safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a child safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
child safety setting may include displaying a different webpage
including only information consistent with a child safety setting
such as "do not display links containing trailers for rated `R`
movies."
[0537] FIG. 43 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24 illustrates example embodiments
where the providing at least one data display option operation 240
may include at least one additional operation. Additional
operations may include an operation 2102, an operation 2104, an
operation 2106, and/or an operation 2108.
[0538] Operation 2102 illustrates displaying alternative data
consistent with a public safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a public safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a public safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a public safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a public safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a public safety setting may include displaying a
different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[0539] Operation 2104 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a home safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a home safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a home safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
home safety setting may include displaying a different webpage
including only information consistent with a home safety setting
such as "do not display links requesting address information."
[0540] Operation 2106 illustrates automatically redirecting to
alternative data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of redirecting to alternative data
(e.g. another website) consistent with a user preference. For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the redirect to alternative data consistent with the user
preference instruction to the data content provider engine 108. The
data content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with the user preference. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then automatically (e.g. prior to alerting a user) display the
alternative data. For instance, a real machine 130 may be
automatically redirected to an acceptable web link, or a page of
acceptable data.
[0541] Further, operation 2108 illustrates providing a list of
selectable alternative data options. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of providing a list of
selectable alternative data options (e.g. a list of alternative
websites) consistent with a user preference. For instance, data
content provider engine 108 may receive at least one provide
selectable alternatives instruction from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to transmit a provide
selectable alternatives instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the provide
selectable alternatives instruction to the data redirection engine
128 to provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data content provider engine 108.
Data content provider engine 108 may then display the list of
selectable alternatives. For instance, the list of selectable
alternative data options may include a list of acceptable web links
or a selectable list of web pages. Selectable web links and web
pages may include a thumbnail image of the first page of the web
link or of the web page.
[0542] FIG. 44 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24 where the providing at least one
data display option operation 230 may include at least one
additional operation. Additional operations may include an
operation 2202, an operation 2204, an operation 2206, and/or an
operation 2208.
[0543] At the operation 2202, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 encompassing
a virtual machine representation of real machine 130, post (e.g.
subsequent to) activation of Link 1, Link 2, and Link 3,
respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. 1B further illustrates virtual machines 11,
12 and/or 13 including a virtual machine representation of content
of the real machine 130 post activation of Link 1, Link 2, and/or
Link 3, respectively. Examples of such content include a movie,
music file, a script (e.g., Java script or Active X control), a
markup language, an email, etc. downloaded onto real machine 130
from one or more sources associated with activation/traversal of
Link 1, Link 2, and/or Link 3. An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation may include determining
an acceptability of an effect of the content of the data at least
in part via a virtual machine representation of at least a portion
of the content of the real machine include determining whether or
not a video or image has been loaded onto, for example, the virtual
machine 11 after loading at least a portion of the data contained
in Link 1.
[0544] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine on a
virtual machine representation of at least a portion of a real
machine generated by, for example, virtual machine 11. FIG. 1C
illustrates a partial follow-on operational view of real machine
130 (e.g., a desktop, notebook, or other type computing system) in
which at least a portion of system 100 (FIG. 1A) has been
implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0545] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6 post traversal of
Link 1. Accordingly, FIG. 1C illustrates system 100 generating
virtual machine representations of real machine 130, used to
traverse Links 4, 5, and 6, in the context of virtual machines 21,
22, and 23, respectively. Those skilled in the art will thus
appreciate that, in the example shown in FIG. 1C, system 100 is
creating second-order virtual machine representations to
prospectively investigate the effects on the states of various
components of real machine 130 via sequential traversals of links.
That is, the virtual machine representations of real machine 130
encompassed in virtual machine 21, virtual machine 22, and virtual
machine 23 of FIG. 1C are generated by system 100 based on the
first-order virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0546] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of content
(e.g., a movie, web page, music file, etc.) of the real machine 130
post sequential activation of Link 1 then Link 4, virtual machine
22 including a virtual machine representation of content (e.g. a
graphical image, a text file, an email, etc) of the real machine
130 post (e.g., subsequent to) sequential activation of Link 1 then
Link 5, and virtual machine 23 encompassing a virtual machine
representation of the content (e.g. a music file) of the real
machine 130 post sequential activation of Link 1 then Link 6. A
determination of an acceptability of an effect of the content of
data on the content of the real machine made on virtual machine 21
may include determining whether or not an audio file has been
loaded onto virtual machine 21. Virtual machine 21 may communicate
a determination of an acceptability of an effect of the content of
data determination made on a virtual machine 21 which may be at
least a portion of content of the real machine to virtual machine
11, which may communicate the acceptability of an effect of the
content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0547] At the operation 2204, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 encompassing
a virtual machine representation of real machine 130, post (e.g.
subsequent to) activation of Link 1, Link 2, and Link 3,
respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. 1B illustrates virtual machine 11 including
a virtual machine representation of software (e.g., a state of
software) of the real machine 130 post (e.g. subsequent to)
activation of Link 1. Examples of such software might include a
commercial word processing program or suite of programs (e.g.
Microsoft.RTM. Office for Windows), an open source Web browser
(e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up (e.g., an
executing JavaScript.TM. and/or data retrieved by same via an
XML-like scheme), or a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware programs (e.g., such as those of Symantec
Corporation or McAfee, Inc.), etc. An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation may include determining
an acceptability of an effect of the content of the data at least
in part via a virtual machine representation of at least a portion
of the software of the real machine include determining whether or
not an unauthorized program or suite of programs (e.g. music
downloading software) has been loaded, for example, onto virtual
machine 12 after loading at least a portion of the data contained
in Link 2.
[0548] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine on a
virtual machine representation of at least a portion of the
software of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link I (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0549] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0550] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
software (e.g.) of the real machine 130 post sequential activation
of Link 1 then Link 4, virtual machine 22 including a virtual
machine representation of software (e.g. an AJAX mashup) of the
real machine 130 post sequential activation of Link 1 then Link 5,
and a virtual machine representation of the software (e.g. a
commercial database management system) of the real machine 130 post
sequential activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the software
of the real machine made on virtual machine 21 may include
determining whether or not malware or grayware has been loaded onto
virtual machine 21. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
software of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0551] At the operation 2206, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the hardware of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 encompassing
a virtual machine representation of real machine 130, post (e.g.
subsequent to) activation of Link 1, Link 2, and Link 3,
respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2 or link 3 actually been traversed on real
machine 130). FIG. 1B illustrates virtual machine 11 including a
virtual machine representation of hardware (e.g. a state of the
hardware) of the real machine 130 post activation of Link 1.
Examples of such hardware might include all or part of a chipset
(e.g., data processor and/or graphics processor chipsets such as
those of Intel Corporation and/or NvidiaCorporation), a memory chip
(e.g., flash memory and/or random access memories such as those of
Sandisk Corporation and/or Samsung Electronics, Co., LTD), a data
bus, a hard disk (e.g., such as those of Seagate Technology, LLC),
a network adapter (e.g., wireless and/or wired LAN adapters such as
those of Linksys and/or CiscoTechnology, Inc.), printer, a
removable drive (e.g., flash drive), a cell phone, etc. An example
of determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a portion of the hardware of the real machine include
determining whether a network adapter on, for example, virtual
machine 12 has been disabled after loading at least a portion of
the data contained in Link 2.
[0552] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine on a
virtual machine representation of at least a portion of the
hardware of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0553] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0554] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
hardware (e.g. the circuitry or processor of the real machine) of
the real machine 130 post sequential activation of Link 1 then Link
4, a virtual machine representation of hardware (e.g. a network
adapter) of the real machine 130 post sequential activation of Link
1 then Link 5, and a virtual machine representation of the hardware
(e.g. a removable drive) of the real machine 130 post sequential
activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the hardware
of the real machine made on virtual machine 21 may include
determining whether a decrease in processor speed of virtual
machine 21 has occurred. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
hardware of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0555] At the operation 2208, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the operating
system of the real machine. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12 and/or 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. FIG. 1B illustrates virtual machines 11,
12 and/or 13 encompassing a virtual machine representation of real
machine 130, post (e.g. subsequent to) activation of Link 1, Link
2, and Link 3, respectively (e.g., as at least a part of real
machine 130 would exist had link 1, link 2, and/or link 3 actually
been traversed on real machine 130). FIG. 1B also illustrates
virtual machine 11 including a virtual machine representation of an
operating system (e.g., a state of an operating system and/or
network operating system) of the real machine 130 post activation
of Link 1. Examples of such an operating system might include a
computer operating system (e.g., e.g. Microsoft.RTM. Windows 2000,
Unix, Linux, etc) and/or a network operating system (e.g., the
Internet Operating System available from Cisco Technology, Inc.
Netware.RTM. available from Novell, Inc., and/or Solaris available
from Sun Microsystems, Inc.). An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a portion of
an operating system of the real machine include determining whether
a portion of the operating system (e.g. Microsoft Vista) on for
example, virtual machine 12 has been disabled after loading at
least a portion of the data contained in Link 2.
[0556] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the operating system of the real machine
may also include determining an acceptability of an effect of the
content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of the operating system of the
real machine on a virtual machine representation of at least a
portion of the operating system of a real machine generated by, for
example, virtual machine 11. FIG. 1C illustrates a partial
follow-on operational view of real machine 130 (e.g., a desktop,
notebook, or other type computing system) in which at least a
portion of system 100 (FIG. 1A) has been implemented (e.g., a
follow-on operational view of the systems/methods illustrated as in
FIG. 1B). Specifically, FIG. 1C illustrates a drill-down view of an
example of the virtual machine 11 including a virtual machine
representation of the content of the real machine 130 post
activation of Link 1 (e.g., a drill-down on the systems/methods
shown/described in relation to FIG. 1B). In this drill down
example, depicted is the virtual machine representation of the
content of the real machine 130 post activation of Link 1.
[0557] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0558] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
operating system (e.g. Linux) of the real machine 130 post
sequential activation of Link 1 then Link 4, a virtual machine
representation of an operating system (e.g. Mac OS/X) of the real
machine 130 post sequential activation of Link 1 then Link 5, and a
virtual machine representation of the operating system (e.g. GNU,
Berkeley Software Distribution) of the real machine 130 post
sequential activation of Link 1 then Link 6 (e.g., as such might
appear after activation of a link installed by a rootkit via
malware/spyware). A determination of an acceptability of an effect
of the content of data on the operating system of the real machine
made on virtual machine 21 may include determining whether or not a
rootkit has been installed onto virtual machine 21. Virtual machine
21 may communicate a determination of acceptability of an effect of
the content of data on a virtual machine representation of at least
a portion of operating system of the real machine made on virtual
machine 21 to virtual machine 11, which may communicate the
acceptability of an effect of the content of data determination to
the virtual machine module 118 (FIG. 1A) for communication to the
Effect of content acceptability determination engine 106 (FIG.
1A).
[0559] FIG. 45 illustrates alternative embodiments of the example
operational flow 200A of FIG. 24 where the providing at least one
data display option operation 230 may include at least one
additional operation. Additional operations may include an
operation 2302, an operation 2304, and/or an operation 2306.
[0560] At the operation 2302, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least a part of a computing device. FIG.
1D illustrates real machine 130 including at least a part of a
computing device 132. The computing device 132 may be any device
capable of processing one or more programming instructions. For
example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[0561] At the operation 2304, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
may spawn virtual machines 11, 12 and/or 13 that may be virtual
machine representations of at least a part of real machine 130.
Real machine 130 may include at least one peripheral device. For
instance, FIG. 1D illustrates real machine 130 including at least
one peripheral device 134-146. FIG. 1D illustrates a representative
view of an implementation of real machine 130 (e.g., a desktop,
notebook, or other type computing system, and/or one or more
peripheral devices) in which a part of system 100 may be
implemented. FIG. 1D illustrates that implementations of real
machine 130 may include all/part of computing device 132 and/or
all/part of one or one or more peripherals associated computing
device 132.
[0562] At the operation 2306, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a part of a real machine having one or more end-user
specified preferences includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 may spawn virtual machines 11, 12 and/or
13 that may be virtual machine representations of at least a part
of real machine 130. Real machine 130 may include at least one
peripheral device. For instance, FIG. 1D illustrates a real machine
may also include at least a portion of one or more peripheral
devices connected/connectable (e.g., via wired, waveguide, or
wireless connections) to real machine 130. Peripheral devices may
include one or more printers 134, one or more fax machines 136, one
or more peripheral memory devices 138 (e.g., flash drive, memory
stick), one or more network adapters 139 (e.g., wired or wireless
network adapters), one or more music players 140, one or more
cellular telephones 142, one or more data acquisition devices 144
(e.g. robots) and/or one or more device actuators 146 (e.g., an
hydraulic arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
Application Ser. No. 12/074,855 (1206-003-007B1-000000)
[0563] Referring to FIG. 46, after a start operation, the
operational flow 200B moves to an operation 210B. Operation 210B
illustrates obtaining at least a portion of data from a data source
(e.g., a server accessible from the internet). For example, FIG. 1A
illustrates a data obtainer engine 102. Data obtainer engine may
obtain (e.g., download) data 110 (e.g., a web page) from a data
source such as a computer accessible from the internet.
[0564] Specifically, data 110 may be web content obtained from the
World Wide Web via a computing device accessible from the internet.
For example, data obtainer engine 102 may set a URL and add a query
string value to the URL. Data obtainer engine 102 may then make a
request to the URL and scan the response received from the URL.
Data 110 may be a web site or web page containing one or more links
to additional web sites, such as shown, for example, in FIG. 1B
and/or FIG. 1C. Data 110 may in some instances be textual, a
two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content. Data obtainer engine 102 may transmit at least a
portion of obtained data to data content determination engine
104.
[0565] Then, operation 220B illustrates determining a content of
the data (e.g., detecting if an image in a link is in jpeg format).
Continuing the example above, FIG. 1A illustrates a data content
determination engine 104. Data content determination engine 104 may
determine the content (e.g., a format/protocol) of at least a
portion of the data 110 obtained from the data source by the data
obtainer engine 102. Data content determination engine 104 may
isolate (e.g., quarantine) at least a portion of the data 110 prior
to determining data content (e.g., video is a Real Networks video).
Data content determination engine 104 may utilize, for example,
pointers or other file format identifiers to determine data
content. For example, data content determination engine 104 may
locate a format specification document within the data content to
determine how data 110 is encoded or determine a format of a data
content by determining a filename extension (e.g., .htm, .gif,
.wav) for the data content or a file format identifier (e.g.,
identifying a file format according to origin and file category)
for the data content. Data content determination engine 104 may
provide Effect of content acceptability determination engine 106
with determined data content information to assist Effect of
content acceptability determination engine 106 to determine an
effect of the content. Data content formats may be any text, image,
audio, and/or video file formats including, but not limited to JPEG
format, or other format designed to store static photographic
images, GIF format, or other format supporting storage of both
still images and/or animations, QuickTime format, Windows Media
Player format, or other format configured to store multiple
multimedia formats.
[0566] Then, operation 230B illustrates determining an
acceptability of an effect of content of the data at least in part
via at least two virtual machine representations of at least a part
of a real machine having at least one end-user specified
preference, at least one of the at least two virtual machine
representations operating at least in part on an individual core of
a multi-core system (e.g., a multi-core processor, a multi-core
system on a chip, etc.). Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive data and an associated data content determination (e.g.,
data content is a Windows Media Audio format audio file) from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and transfer of obtained data to data content
determination engine 106. Data content determination engine may
provide Effect of content acceptability determination engine 106
with information regarding a format/protocol of content at least a
portion of the data. Effect of content acceptability determination
engine 106 may utilize format/protocol information to determine
whether Effect of content acceptability determination engine should
call a specific database or library (e.g., a Windows Media Player
library) to obtain file format information. File format information
may be utilized to compare received data content to data stored in
a library. Effect of content acceptability determination engine 106
(FIG. 1A) may utilize, for example, virtual machine 12 (FIG. 1A)
spawned by virtual machine module 118 on an individual core of a
multi-core system to determine whether data associated with Link 2
would result in a change in the operating system of real machine
130 contra to user preferences regarding the operating system as
reflected by user preference database 120.
[0567] Then, operation 240B illustrates displaying at least one
data display option based on the determining an acceptability of a
content of the data. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
transfer at least one effect of content acceptability determination
(e.g., content contains malware) to the data content provider
engine 108. Data content provider engine 108 may provide at least
one data display option (e.g., displaying a message that content
will not display) to a user based on the received effect of content
acceptability determination. In one example, data provider engine
108 provides data via placing the data on a visual display, where
the content is such that it meets one or more thresholds associated
with the effect of content acceptability determination 106.
Provided data may be a list of web links, a web page, or other data
that either have been deemed acceptable by effect of content
acceptability determination engine 106 or that have been modified
(e.g., obfuscated), such as by data modification engine 122, such
that the to-be-displayed content is judged acceptable under user
preferences. Provided data may be modified via the data
modification engine 122. For instance, provided data may be
obfuscated via the data obfuscation engine 124 (e.g., at least a
portion of the displayed data may be blurred out or disabled), or
provided data may be anonymized via the data anonymization engine
126 (e.g., at least a portion of the data may be deleted entirely).
Data content provider engine 108 (FIG. 1A) may receive at least one
display instruction (e.g., OK to display links 1 and 2) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A) for at least a portion of data
to be displayed. For instance, at least one of virtual machines 11,
12, and/or 13 may include one or more instruction generating
modules configured to provide an instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Such instruction may include an
instruction to the data content provider engine 108 to prevent the
data content provider engine 108 from displaying data that may
configure a hardware profile of real machine 130 counter to
anti-viral settings stored in the user preference database 120
(FIG. 1A), or an instruction to the data content provider engine
108 to prevent the data content provider engine 108 from displaying
data that may configure an operating system of real machine 130
counter to a previous operating system of the real machine 130
(e.g., determine if a rootkit has been installed).
[0568] FIG. 47 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 220B may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[0569] The operation 302 illustrates examining a database of known
content for data content information. Continuing the example above,
data content determination engine 104 (FIG. 1A) may transmit at
least a portion of data content to a database examination engine
112 to extract data content information from at least a portion of
the data. A database examination engine 112 may examine (e.g.,
scan) a database (e.g., information obtained from a storage server)
of known data (e.g., a database of known audio formats) and compare
the known data to the data 110 to determine data content (e.g.,
audio content is in mp3 format). Data content determination may be
transmitted from the database examination engine 112 to the data
content determination engine 104, and the data content
determination engine 104 may subsequently transmit the data content
determination to the Effect of content acceptability determination
engine 106. Database examination engine 112 may be--configured to
examine a database of data provided, for example, by a data
provider service or a database of data stored on a real machine
130. For instance, a database may include a list of links viewed by
a user or pre-approved by a user based on one or more
user-specified preferences, such as links from a specific source of
information (e.g., the Roman Catholic Church).
[0570] The operation 304 illustrates traversing at least a portion
of the data in real time. Continuing the example above, data
content determination engine 104 (FIG. 1A) may transmit at least a
portion of data content to a data transverser engine 114 to extract
data content information from at least a portion of the data. A
data transverser engine 114 may traverse (e.g., parse) at least a
portion of the data (e.g., a portion of a web page) to determine a
format for at least a portion of data content (e.g., an image
format or video format) within the portion of the data. Data
traversal may occur in real time (e.g., simultaneously as data is
loading). Data content determination may be transmitted from the
data transverser engine 114 to the data content determination
engine 104, and the data content determination engine 104 may
subsequently transmit the data content determination to the Effect
of content acceptability determination engine 106.
[0571] The operation 306 illustrates locally examining at least a
portion of the data. Continuing the example above, data content
determination engine 104 may transmit at least a portion of data
content to a local data examination engine 116 (FIG. 1A) to extract
data content information from at least a portion of the data. A
local data examination engine 116 may locally (e.g., on the real
machine 130) examine (e.g., analyze) at least a portion of the data
(e.g., one or more pointers in the data) to determine data content
(e.g., an audio file is a .wav file). For instance, local data
examination engine 116 may view an amount of html source code to
locate markers signifying the format of at least a portion of data
content. Data content determination may be transmitted from the
local data examination engine 116 to the data content determination
engine 104. Data content determination engine 104 may transmit a
data content determination to the Effect of content acceptability
determination engine 106.
[0572] FIG. 48 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, and/or an operation
406.
[0573] The operation 402 illustrates examining at least a portion
of the data to locate references to additional content. Continuing
the example above, Effect of content acceptability determination
engine 106 (FIG. 1A) may receive a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, and/or 13 (FIG. 1B). Each of
virtual machines 11, 12, and/or 13 may examine (e.g., scan) at
least a portion of data (e.g., an imbedded link on a webpage) to
determine if the data references additional content (e.g., one or
more additional images). Additional content may be a web page
comprising text and/or an image, a link to a web page, a video or
any combination of text, images, links to web pages, or videos.
Virtual machines 11, 12, and/or 13 may traverse additional data to
determine an acceptability of an effect of the data content. Effect
of content acceptability determination may be communicated to
Effect of content acceptability determination engine 106 (FIG. 1A)
that may communicate an effect of content acceptability
determination to a data provider engine 108 (FIG. 1A).
[0574] The operation 404 illustrates determining whether the data
references additional data content information when loading.
Continuing the example above, Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post obtaining of data
by data obtainer engine 102 and communication of obtained data to
data content determination engine 104. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. Any of virtual machines 11, 12, and/or 13 may examine the data
in real time as it loads onto the virtual machine 11, 12, and/or 13
to determine if the data (e.g., Link 1) references additional data
(e.g., Link 4) when loading. For instance, if a link to a webpage
immediately (e.g., as soon as the link is activated) references an
additional link (e.g., to redirect a user), a virtual machine 11,
12, and/or 13 may determine that such a reference to an additional
link has been made. Virtual machines 11, 12, and/or 13 may
determine whether data references additional data at any time when
the data is loading. Effect of content acceptability determination
engine 106 (FIG. 1A) may communicate an effect of content
acceptability determination to a data provider engine 108 (FIG.
1A).
[0575] The operation 406 illustrates issuing a request to a remote
computer for additional data content information. Continuing the
example above, Effect of content acceptability determination engine
106 (FIG. 1A) may receive a data content determination from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 on at
least one core of a multi-core system including, for example, cores
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or 13
(FIG. 1B). Each of virtual machines 11, 12, and/or 13 may examine
(e.g., scan) at least a portion of data (e.g., an imbedded link on
a webpage) to determine if the data references additional data
(e.g., one or more additional links). Additional data may be a web
page comprising text and/or an image, a link to a web page, a video
or any combination of text, images, links to web pages, or videos.
Virtual machines 11, 12, and/or 13 may traverse additional data to
determine an acceptability of an effect of the data content. Effect
of content acceptability determination may be communicated to
Effect of content acceptability determination engine 106 (FIG. 1A)
that may communicate an effect of content acceptability
determination to a data provider engine 108 (FIG. 1A).
[0576] FIG. 49 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 502, and/or an operation 504.
[0577] The operation 502 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least two virtual machine representations operating
at least in part on an individual core of a multi-core system at
least partially resident within a real machine. Continuing the
example above, Effect of content acceptability determination engine
106 (FIG. 1A) may receive a data content determination from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, and/or 13. In one
implementation, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may be generated on the real machine 130 (e.g., as a
subsystem of real machine 130).
[0578] The operation 504 illustrates determining an acceptability
of an effect of content of the data at-least in part via at least
two virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least two virtual machine representations operating
at least in part on an individual core of a multi-core system at
least partially non-resident within a real machine. Continuing the
example above, Effect of content acceptability determination engine
106 (FIG. 1A) may receive a data content determination from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118 including virtual machines 11, 12,
and 13. In one implementation, at least one of virtual machines 11,
12, and/or 13 may be generated on a remote server, remote operating
system or otherwise geographically distinct location with respect
to the real machine 130.
[0579] FIG. 50 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 602, and/or an operation 604.
[0580] The operation 602 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of
content of a real machine. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102. Effect of content acceptability determination engine
106 may transfer data received from data content determination
engine 104 following a determination of data content. Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to the virtual
machine module 118. Virtual machine module 118 (FIG. 1A) may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least-one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
further illustrates virtual machines 11, 12, and 13 including a
virtual machine representation of content of the real machine 130
post activation of Link 1, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
email, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation may include determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine include determining whether or not a video or image
has been loaded onto, for example, the virtual machine 11 after
loading at least a portion of the data contained in Link 1.
[0581] The operation 604 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of
software of a real machine. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102. Effect of content acceptability determination engine
106 may transfer data received from data content determination
engine 104 following a determination of data content. Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to the virtual
machine module 118. Virtual machine module 118 (FIG. 1A) may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software, such as a
state of Windows Media Player) of the real machine 130 post (e.g.,
subsequent to) activation of Link 1. Examples of such software
might include a commercial word processing program or suite of
programs (e.g., Microsoft.RTM. Office for Windows), an open source
Web browser (e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up
(e.g., an executing JavaScript.TM. and/or data obtained by same via
an XML-like scheme), a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware program (e.g., such as those of Symantec
Corporation or McAfee, Inc.), a multi-media program (e.g.,
QuickTime) etc. An example of determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation may include determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine include determining whether or not an unauthorized
program or suite of programs (e.g., music downloading software) has
been loaded, for example, onto virtual machine 12 after loading at
least a portion of the data contained in Link 2.
[0582] FIG. 51 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 702, and/or an operation 704.
[0583] The operation 702 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of
hardware of a real machine. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and may transfer data received from data content
determination engine 104 following a determination of data content.
Effect of content acceptability determination engine 106 may
transfer the--data and "associated data content determination to
the virtual machine module 118. FIG. 1B illustrates virtual machine
11 including a virtual machine representation of hardware (e.g., a
state of the hardware) of the real machine 130 post activation of
Link 1. Examples of such hardware might include all or part of a
chipset (e.g., data processor and/or graphics processor chipsets
such as those of Intel Corporation and/or NvidiaCorporation), a
memory chip (e.g., flash memory and/or random access memories such
as those of Sandisk Corporation and/or Samsung Electronics, Co.,
LTD), a data bus, a hard disk (e.g., such as those of Seagate
Technology, LLC), a network adapter (e.g., wireless and/or wired
LAN adapters such as those of Linksys and/or CiscoTechnology,
Inc.), printer, a removable drive (e.g., flash drive), a cell
phone, etc. An example of determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of the hardware of the real
machine includes determining whether a network adapter on, for
example, virtual machine 12 has been disabled after loading at
least a portion of the data contained in Link 2.
[0584] The operation 704 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of an
operating system of a real machine. Continuing the example above,
Effect of content acceptability determination engine 106 (FIG. 1A)
may receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102. Effect of content acceptability determination engine
106 may transfer data received from data content determination
engine 104 following a determination of data content. Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to the virtual
machine module 118. Virtual machine module 118 (FIG. 1A) may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had link 1, link 2,
and/or link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of an operating system (e.g., a state of an
operating system and/or network operating system) of the real
machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or a network
operating system (e.g., the Internet Operating System available
from Cisco Technology, Inc. Netware.RTM. available from Novell,
Inc., and/or Solaris available from Sun Microsystems, Inc.). An
example of determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of an operating system of the real machine
include determining whether a portion of the operating system
(e.g., Microsoft Vista) on for example, virtual machine 12 has been
disabled after loading at least a portion of the data contained in
Link 2.
[0585] FIG. 52 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 802, an operation 804, and/or an operation
806.
[0586] The operation 802 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of a real machine including at
least a portion of a computing device. FIG. 1D illustrates real
machine 130 including at least a part of a computing device 132.
The computing device 132 may be any device capable of processing
one or more programming instructions. For example, the computing
device 132 may be a desktop computer, a laptop computer, a notebook
computer, a mobile phone, a personal digital assistant (PDA),
combinations thereof, and/or other suitable computing devices.
[0587] The operation 804 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of a real machine including at
least one peripheral device. Continuing the example above, Effect
of content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and communication of obtained data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 may spawn at least one of virtual
machines 11, 12, and/or 13 that may be a virtual machine
representation of at least a part of real machine 130. Real machine
130 (FIG. 1B) may include at least one peripheral device. For
instance, FIG. 1D illustrates real machine 130 including at least
one peripheral device 134-146. FIG. 1D illustrates a representative
view of an implementation of real machine 130 (e.g., a desktop,
notebook, or other type computing system, and/or one or more
peripheral devices) in which all/part of system 100 may be
implemented. FIG. 1D illustrates that implementations of real
machine 130 may include all/part of computing device 132 and/or a
part of one or one or more peripherals associated computing device
132.
[0588] Further, the operation 806 illustrates determining an
acceptability of an effect of content of the data at least in part
via at least two virtual machine representations of a real machine
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, Effect
of content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and communication of obtained data to data content
determination engine 104. Virtual machine module 118 (FIG. 1A) may
spawn at least one of virtual machines 11, 12, and/or 13 that may
be a virtual machine representation of at least a part of real
machine 130. Real machine 130 may include at least one peripheral
device. For instance, FIG. 1D illustrates a real machine may also
include at least a portion of one or more peripheral devices
connected/connectable (e.g., via wired, waveguide, or wireless
connections) to real machine 130. Peripheral devices may include
one or more printers 134, one or more fax machines 136, one or more
peripheral memory devices 138 (e.g., flash drive, memory stick),
one or more network adapters 139 (e.g., wired or wireless network
adapters), one or more music players 140, one or more cellular
telephones 142, one or more data acquisition devices 144 (e.g.,
robots) and/or one or more device actuators 146 (e.g., an hydraulic
arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
[0589] FIG. 53 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 902, and/or an operation 904.
[0590] The operation 902 illustrates determining a state of at
least one of the at least two virtual machine representations
operating at least in part on an individual core of a multi-core
system prior to loading at least a portion of the data. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106 including a virtual machine
module 118, further including at least one of virtual machines 11,
12, and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post obtaining of data
by data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may determine a state of at least one component (e.g., the
hardware) of the virtual machine prior to activation (e.g., before)
of a link. Virtual machine state may be representative of a state
for all or at least a portion of the components (e.g., content,
software, hardware, operating system) of the real machine 130
represented by the virtual machine 11, 12, and/or 13. For instance,
at least one of virtual machines 11, 12, and/or 13 may be
determined to be free of viruses, an amount of virtual machine
memory may be measured, or a processing speed of at least one of
virtual machines 11, 12, and/or 13 may be determined. At least one
of virtual machines 11, 12, and/or 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[0591] The operation 904 illustrates determining a state of at
least one of the at least two virtual machine representations
operating at least in part on an individual core of a multi-core
system subsequent to loading at least a portion of the data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12,
and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post obtaining of data
by data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may determine a state of at least one component (e.g., the
hardware) of the virtual machine subsequent to (e.g., after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by at least one of virtual machines 11, 12, and/or 13
after at least a portion of the data has loaded. For instance, at
least one of virtual machines 11, 12, and/or 13 may be determined
to contain a virus, an amount of virtual machine memory may be
measured, or a processing speed of at least one of virtual machines
11, 12, and/or 13 may be determined. At least one of virtual
machines 11, 12, and/or 13 may be examined to determine, for
example, if a virus or any other undesired software is present on
the machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[0592] FIG. 54 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1002, and/or an operation 1004.
[0593] The operation 1002 illustrates determining a state change of
at least one of the at least two virtual machine representations
operating at least in part on an individual core of a multi-core
system between a prior state and a subsequent state of at least one
of the at least two virtual machine representations operating at
least in part on an individual core of a system comprising at least
two cores after loading at least a portion of the data. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106 including a virtual machine
module 118 further including virtual machines 11, 12, 13. Upon
receiving data and a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. A state change (e.g., a
decrease in memory) of at least one of virtual machines 11, 12,
and/or 13 (FIG. 1B) may be determined by a component of at least
one of virtual machines 11, 12, and/or 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[0594] Further, the operation 1004 illustrates determining whether
a state change on at least one of the at least two virtual machine
representations operating at least in part on an individual core of
a multi-core system is an undesirable state change based on one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer the data
and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. An undesirable state change may
be determined by examining the changes to at least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) and comparing the state change
of at least one of virtual machines 11, 12, and/or 13 to user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. 1A)
onto at least one of virtual machines 11, 12, and/or 13. A state
change may include any undesirable state changes such as a decrease
in memory or processing speed and/or the presence of a virus or
other undesirable software after at least a portion of the data has
loaded. Undesirable state changes may further include an
undesirable transfer of information located on at least one of
virtual machines 11, 12, and/or 13 to an external location, an
undesirable transfer of data onto at least one of virtual machines
11, 12, and/or 13 from an external location after at least a
portion of the data has loaded on at least one of virtual machines
11, 12, and/or 13 that may result in an undesired change in the
state of content, software, hardware or an operating system of the
real machine 130 and/or an undesirable transfer of data onto at
least one of virtual machines 11, 12, and/or 13 where at least a
portion of the transferred data may be found objectionable when
viewed by a user 10.
[0595] FIG. 55 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1102, an operation 1104, and/or an
operation 1106.
[0596] The operation 1102 illustrates determining an acceptability
of an effect of content of the data in response to at least one
user setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. An acceptability of an effect of content of the data may be
determined by determining if a state change to at least one of
virtual machines 11, 12, and/or 13 has occurred and comparing the
state change of at least one of virtual machines 11, 12, and/or 13
to user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Comparison may be made, for
example by transferring user preference database information from
the user preference database 120 (FIG. 1A) to the virtual machine
module 118 (FIG. 1A) which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one end-user specified preference relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. At least one of virtual machines 11,
12, and/or 13 may determine an acceptability of an effect of the
content of the data based on at least one user setting contained in
a user preference database at least a portion of which may be
spawned onto at least one of virtual machines 11, 12, and/or 13 via
virtual machine module 118 (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a setting established by a user such as a political or
cultural preference setting). Further examples of user preferences
include specific religion or lifestyle preference, such as "return
only links relating to Roman Catholicism" or "return only links
relating to a vegan lifestyle" that may be stored in the real
machine 130. User-specific preference may also relate to user
information safety or computer safety, such as "do not display
links requesting information from my computer," or "do not display
links that transfer viruses onto my computer."
[0597] Further, the operation 1104 illustrates determining an
acceptability of an effect of content of the data in response to a
personal user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a personal user
setting (e.g., "show only automobile related data") contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one personal user setting relating to at least
one of content, software, hardware and/or an operating system of a
real machine 130. Personal user setting may be a setting input by a
user that is personal to the user, such as an information security
level, a content filter level, or a personal desirability setting
such as "show only non-religious data" or "show only automobile
related data."
[0598] Further, the operation 1106 illustrates determining an
acceptability of an effect of content of the data in response to a
peer user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, and 13. Upon receiving data and a data
content determination from data content determination engine 104
post obtaining of data by data obtainer engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine. 1.1.cndot., 12, and/or 13 and transfer data
and--associated data content determination. to at least one of
virtual machines 11, 12, and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
may compare the data received from the virtual machine module to a
peer user setting contained in user preference database information
spawned on at least one of virtual machines 11, 12, and/or 13. User
preference database 120 may include at least one peer user setting
relating to at least one of content, software, hardware and/or an
operating system of a real machine 130. Peer user setting may be a
setting input by a user that is determined by a peer group, such as
a peer group determined information security level such as "display
only 100 percent secure websites", a peer group determined data
filter level such as "filter 100% of obscene data", or a peer group
desirability setting such as "show only classical music related
data" or "show only knitting related data."
[0599] FIG. 56 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1202, and/or an operation 1204.
[0600] The operation 1202 illustrates determining an acceptability
of an effect of content of the data in response to a corporate user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a corporate user
setting contained in user preference database information spawned
on at least one of virtual machines 11, 12, and/or 13. User
preference database 120 may include at least one corporate user
setting relating to at least one of content, software, hardware
and/or an operating system of a real machine 130. Corporate user
setting may be a setting input by a corporation that is determined
to the corporation, such as a corporate desirability setting such
as "show only real-estate related data" or "show only agricultural
related data."
[0601] The operation 1204 illustrates determining an acceptability
of an effect of content of the data in response to a work safety
user setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a work safety user
setting contained in user preference database information spawned
on at least one of virtual machines 11, 12, and/or 13. User
preference database 120 may include at least one work safety user
setting relating to at least one of content, software, hardware
and/or an operating system of a real machine 130. Thus, in one
specific example, a webpage or website data may be determined to be
displayable if the data satisfies a work safety user setting such
as a corporate information security level, corporate user setting,
or a corporate information content filter level corporate user
setting.
[0602] FIG. 57 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1302, an operation 1304, and/or an
operation 1306.
[0603] The operation 1302 illustrates determining an acceptability
of an effect of content of the data in response to a desirability
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a desirability
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a desirability
setting established by a user such as a desire to view only
non-obscene material) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. User preference database 120 may include at least one
desirability setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130.
[0604] Further, the operation 1304 illustrates determining an
acceptability of an effect of content of the data in response to a
religious desirability setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 may compare the data received from the
virtual machine module 118 to a religious desirability setting
(e.g., does a website contain only images, text, audio or visual
data suitable for viewing by a user based on a religious
desirability setting established by a user such as a desire to view
only Hindu material) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A religious desirability setting may be include any
setting regarding a major, minor, or other religion such as
Christianity, Judaism, Islam, Hinduism, and so on.
[0605] Further, the operation 1306 illustrates determining an
acceptability of an effect of content of the data in response to a
political desirability setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a political
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a political desirability setting established by a user such as a
desire to view only Democratic Party material) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A political desirability setting may
include any setting regarding a political party or affiliation
(e.g., Republican, Democratic, Libertarian, Green Party, etc.).
[0606] FIG. 58 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1402, and/or an operation 1404.
[0607] The operation 1402 illustrates determining an acceptability
of an effect of content of the data in response to a cultural
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a cultural
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a cultural desirability setting established by a user such as a
desire to view only materials regarding early Mayan civilization)
contained in user preference database information spawned on at
least one of virtual machines 11, 12, and/or 13. A cultural
desirability setting may include any culturally related information
such as a religious, ethnic, regional, or heritage based cultural
desirability setting or any other cultural desirability
setting.
[0608] Further, the operation 1404 illustrates determining an
acceptability of an effect of content of the data in response to a
theme related desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, and/or 13. User preference database information
stored in the user preference database 120 (FIG. 1A) may be
transferred to the virtual machine module 118 (FIG. 1A), which
spawns a copy of at least a portion of the user preference database
120 (FIG. 1A) onto at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a theme related desirability setting (e.g., does a
website contain only images, text, audio or visual data suitable
for viewing by a user based on a theme related desirability setting
established by a user such as a desire to view only materials
regarding collectible stamps) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A theme related desirability setting may include any
theme related information, such as information relating to cars,
fashion, electronics, sports, hobbies, collector's items, or any
theme or category that may be of interest to a user.
[0609] FIG. 59 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1502.
[0610] The operation 1502 illustrates determining an acceptability
of an effect of content of the data in response to an age
appropriateness desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, and/or 13. User preference database information
stored in the user preference database 120 (FIG. 1A) may be
transferred to the virtual machine module 118 (FIG. 1A), which
spawns a copy of at least a portion of the user preference database
120 (FIG. 1A) onto at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to an age appropriateness desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on an age appropriateness
desirability setting established by a user such as a desire to view
only materials given a PG or lower rating as determined by the
Motion Picture of America Association film rating system) contained
in user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. An age appropriateness
desirability setting may include any age appropriate setting, such
as a rating threshold or a profanity threshold.
[0611] FIG. 60 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1602, an operation 1604, and/or an
operation 1606.
[0612] The operation 1602 illustrates determining an acceptability
of an effect of content of the data in response to at least one
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a privacy related
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a privacy
related setting established by a user) contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. A privacy related setting may include any
privacy related settings (e.g., does a website contain only data
that will not request information from my computer or allow others
to view personal information saved on my computer).
[0613] Further, the operation 1604 illustrates determining an
acceptability of an effect of content of the data in response to a
user specific privacy related setting. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination-to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, and/or 13. User preference database information
stored in the user preference database 120 (FIG. 1A) may be
transferred to the virtual machine module 118 (FIG. 1A), which
spawns a copy of at least a portion of the user preference database
120 (FIG. 1A) onto at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a user specific privacy related setting (e.g., will a
website request specific information about the user such as name,
address, telephone number) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A user specific privacy related setting may include any
user specific privacy related settings (e.g., a setting relating to
a user's biographical information or financial information).
[0614] Further, the operation 1606 illustrates determining an
acceptability of an effect of content of the data in response to a
group privacy related setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a group privacy
related setting (e.g., will a website request information about an
organization such as name, address, telephone number) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. A group privacy related setting
may include any group privacy related settings (e.g., a setting
relating to a group's membership). Group privacy related setting
may be any setting established by a group such as a work group
(e.g., employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g., members of family unit)
privacy related setting.
[0615] FIG. 61 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1702, and/or an operation 1704.
[0616] The operation 1702 illustrates determining an acceptability
of an effect of content of the data in response to a corporate
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a corporate
privacy related setting (e.g., will a website request information
about a corporation such as data stored on a real machine belonging
to the corporation) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Corporate privacy related setting may be determined by a
corporate-issued privacy manual, or other such document or mandate
set forth by officers of a corporation.
[0617] Further, the operation 1704 illustrates determining an
acceptability of an effect of content of the data in response to
transmitted user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to at least one
acceptable type of transmitted user information setting (e.g., do
not return links that will transmit my e-mail address, home address
or telephone number to an external location) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. Acceptable type of transmitted user
information setting may be determined by a user 10 (FIG. 1B). For
instance, acceptability of the effect of the data may be determined
in response to whether or not private user information, such as
credit card numbers, bank accounts, personal identification
information or any other personal user information may be
transmitted to a location external to the real machine by selecting
the link.
[0618] FIG. 62 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1802, and/or an operation 1804.
[0619] The operation 1802 illustrates determining an acceptability
of an effect of content of the data in response to captured user
information. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to at least one
acceptable type of captured user information setting (e.g., do not
return links that will capture my e-mail address, home address or
telephone number) contained in user preference database information
spawned on at least one of virtual machines 11, 12, and/or 13.
Acceptable type of captured user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be captured by a machine located at a location
external to the real machine by selecting the link.
[0620] Further, the operation 1804 illustrates determining an
acceptability of an effect of content of the data in response to
exposed user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may--transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to at least one
acceptable type of exposed user information setting (e.g., do not
return links that will expose personal financial information stored
on the real machine 130) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Acceptable types of exposed user information settings
may be determined by a user 10 (FIG. 1B). For instance,
acceptability of the effect of the data may be determined in
response to whether or not private user information, such as credit
card numbers, bank accounts, personal identification information or
any other personal user information may be exposed to a machine
located at a location external to the real machine by selecting the
link.
[0621] FIG. 63 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 230B may
include at least one additional operation. Additional operations
may include an operation 1902, and/or an operation 1904.
[0622] The operation 1902 illustrates determining an acceptability
of an effect of content of the data in response to visually
examining at least a portion of a data image on at least one of the
at least two virtual machine representations operating at least in
part on an individual core of a multi-core system. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106 including a virtual machine
module 118 further including virtual machines 11, 12, 13. Upon
receiving data and a data content determination from data content
determination-engine 104 post obtaining of data by data obtainer
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. To visually examine a data
image, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may include an image scanning module. Visually examining the data
image may include, for example, color analysis, pattern-matching,
pattern-recognition, or any other technique for recognizing a
particular image or type of image.
[0623] The operation 1904 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
three virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least three virtual machine representations operating
at least in part on an individual core of a multi-core system
comprising at least three cores (i.e. chip-level multiprocessor).
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118, further including virtual machines 11, 12,
and/or 13 operating on Cores 11, 12, and/or 13, respectively of a
multi-core system. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. At least one of virtual machines 11, 12, and/or 13 may
determine a state of at least one component (e.g., the hardware) of
the virtual machine prior to activation (e.g., before) of a link.
Virtual machine state may be representative of a state for all or
at least a portion of the components (e.g., content, software,
hardware, operating system) of the real machine 130 represented by
the virtual machine 11, 12, and/or 13. Multi-core system may
include at least one additional core, such as, for instance, Core
31 (FIG. 1C); Core 32 (FIG. 1C) and/or Core 33 (FIG. 1C).
[0624] FIG. 64 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2002, and/or an operation 2004.
[0625] The operation 2002 illustrates providing a data display
option of displaying at least a portion of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g., data is a video file) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying at least a portion
of the data. For instance, data content provider engine 108 may
receive at least one display instruction (e.g., OK to display the
entire text of link 1) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. Data content
provider engine 108 may then display the data. Displayed data may
be an unmodified web page of text, images and/or video, or a web
page including links to additional web pages and may be displayed
on a real machine display such as a computer screen.
[0626] The operation 2004 illustrates providing a data display
option of not displaying at least a portion of the data. Continuing
the example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g., data is a video file) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of not displaying at least a
portion of the data. For instance, data content provider engine 108
may receive at least one do not display instruction (e.g., Do not
display the text of link 1) from at least one component of Effect
of content acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
include one or more instruction generating modules configured to
provide a do not display instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the do not display instruction to the
data content provider engine 108. The data display option of not
displaying the data may include a message indicated why the data is
not being displayed, or may be, for example, a blank page displayed
on a display of the real machine.
[0627] FIG. 65 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2102, an operation 2104, and/or an
operation 2106.
[0628] The operation 2102 illustrates providing a data display
option of displaying a modified version of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g., data is a video file) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying at least a portion
of the data. For instance, data content provider engine 108 (FIG.
1A) may receive at least one modify data instruction (e.g., display
only lines 1-10 of the text of link 1) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide a
modify data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the modify data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
may transmit the modified data to the data content provider engine
108. Data content provider engine 108 may then display the modified
version of the data. Displayed data may be a modified web page of
text, a modified image and/or a modified video, or a modified web
page including links to additional web pages. For instance, a
webpage or website may be displaying, but any obscenities on the
web page or website may replaced by non-obscene word
alternatives.
[0629] Further, the operation 2104 illustrates providing a data
display option of obfuscating an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data is a video file)
from data content determination engine 104 (FIG. 1A) post obtaining
of data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of obfuscating (e.g., blurring)
a portion of the data (e.g., obscene photos). For instance, data
content provider engine 108 may receive at least one obfuscate data
instruction (e.g., display only non-obscene portions of the image
in link 1) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 (FIG. 1B) may include one or
more instruction generating modules configured to provide an
obfuscate data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the obfuscate data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the obfuscate data instruction to the data modification
engine 122 which may transmit the obfuscate data instruction to the
data obfuscation engine 124. Data obfuscation engine 124 may
transmit the obfuscated data to the data modification engine 122
for transmission to the data content provider engine 108. Data
content provider engine 108 may then display the obfuscated version
of the data. For example, obfuscating logic may obfuscate
restricted data or imagery within a webpage or image. Obfuscation
may include blurring or blocking of the objectionable data
portion.
[0630] Further, the operation 2106 illustrates providing a data
display option of anonymizing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data entails a video
file of wmv format) from data content determination engine 104
(FIG. 1A) post obtaining of data by data obtainer engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination and an
instruction to the data provider engine 108 to provide the data
display option of anonymizing (e.g., obscuring source information)
for a portion of the data (e.g., graphic videos). For instance,
data content provider engine 108 may receive at least one anonymize
data instruction (e.g., obscure source information for portions of
the video in link 1) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an anonymize
data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the anonymize data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the anonymize data instruction to the data modification
engine 122 which may transmit the anonymize data instruction to the
data anonymization engine 126. Data anonymization engine 126 may
transmit the anonymized data to the data modification engine 122
for transmission to the data content provider engine 108. Data
content provider engine 108 may then display the anonymized version
of the data. Anonymized data may be data in which the original
identity information of the data is hidden, obscured, replaced,
and/or otherwise modified.
[0631] FIG. 66 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2202.
[0632] The operation 2202 illustrates providing a data display
option of at least one of removing, altering or replacing an
objectionable data portion. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination
(e.g., data entails an audio file of MP3 format) from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination and an instruction to the data provider
engine 108 to provide the data display option of removing, altering
or replacing an objectionable data portion (e.g., replacing
profanity with innocuous language) for a portion of the data (e.g.,
explicit lyrics). For instance, data content provider engine 108
may receive at least one alter, remove or replace instruction
(e.g., obscure source information for portions of the video in link
1) from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a remove, alter or replace
data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the remove, alter or replace data instruction to the
data content provider engine 108. The data content provider engine
108 may transmit the anonymize data instruction to the data
modification engine 122 which may then remove, alter or replace the
data. Data modification engine 122 may transmit the data containing
removed, altered or replaced portions to the data content provider
engine 108. Data content provider engine 108 may then display the
data containing removed, altered, or replaced portions. Thus, in
one specific example, a portion of a webpage produced by a search
including data relating to religions other than Catholicism may be
removed from the web page prior to display of the data on a real
machine display such as a computer screen.
[0633] FIG. 67 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2302, and/or an operation 2304.
[0634] The operation 2302 illustrates providing a data display
option of displaying a data portion consistent with at least one
user-related setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one user setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g., OK
to display webpage) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If displayed
data needs to be modified to be consistent with at least one user
setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 (FIG. 1A) may transmit the modified data to the data content
provider engine 108. Data content provider engine 108 may then
display the data consistent with the user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a user setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the user setting. For instance,
a portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[0635] Further, the operation 2304 illustrates providing a data
display option of displaying a data portion consistent with a
privacy related user setting. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination from
data content determination engine 104 (FIG. 1A) post obtaining of
data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one privacy related setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g., OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide an instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a privacy related setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, 13. Effect of content acceptability determination engine
106 may communicate the display instruction to the data content
provider engine 108. If displayed data needs to be modified to be
consistent with at least one privacy related setting, the data
content provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data consistent
with the privacy related setting. For instance, a portion of a
returned webpage including data requesting private user information
such as a user's social security number or e-mail address may be
removed from the web page prior to display of the data on a
computer screen. Further specific examples include a webpage or
website data may be determined to be displayable if the data
satisfies a setting such as a privacy related setting such as a
setting relating to a user's biographical information or financial
information, a webpage or website data may be determined to be
displayable if the data satisfies a group privacy related setting
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting, or a webpage or website data
may be determined to be displayable if the data satisfies a privacy
setting determined by a corporation or other organization to
maintain corporate or organization privacy.
[0636] FIG. 68 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2402.
[0637] The operation 2402 illustrates providing a data display
option of displaying a data portion consistent with a desirability
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g., data
entails an image of format JPEG) from data content determination
engine 104 (FIG. 1A) post obtaining of data by data obtainer engine
102 (FIG. 1A). Effect of content acceptability determination engine
106 may transfer effect of content acceptability determination to
the data provider engine 108 to provide the data display option of
displaying data consistent with at least one desirability setting.
For instance, data content provider engine 108 may receive at least
one display instruction (e.g., OK to display image) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If displayed data needs to be modified
to be consistent with at least one desirability setting, the data
content provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data portion
consistent with the desirability setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with a Christian desirability
setting such as "display only Christianity related data." In other
examples, a webpage or website data may be determined to be
displayable if the data satisfies a desirability setting, a webpage
or website data may be determined to be displayable if the data
satisfies a religious desirability setting such as a Christian,
Jewish, and/or Muslim, based religious desirability setting, or may
be based on any other major, minor or alternative religious
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a political desirability
setting such as a Republican, Democratic, Libertarian or Green
Party political desirability setting, a webpage or website data may
be determined to be displayable if the data satisfies a cultural
desirability setting such as a religious, ethnic, regional, or
heritage based cultural desirability setting or any other cultural
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a theme related
desirability setting such as boating or card games, or a webpage or
website data may be determined to be displayable if the data
satisfies an age appropriateness desirability setting such as a
setting based on the Motion Picture of America Association film
rating system.
[0638] FIG. 69 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2502.
[0639] The operation 2502 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace established setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g., do not display data) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace established setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, 13. Effect of content acceptability determination engine
106 may communicate the display instruction to the data content
provider engine 108. If displayed data needs to be modified to be
consistent with at least one workplace established setting, the
data content provider engine 108 (FIG. 1A) may transmit the modify
data instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data portion
consistent with the workplace established setting. For instance,
the data display option may be displaying on a display of a real
machine only a data portion consistent with a workplace
appropriateness desirability setting such as "display only
non-obscene data."
[0640] FIG. 70 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2602, and/or an operation 2604.
[0641] The operation 2602 illustrates providing a data display
option of displaying a data portion consistent with a safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g., data is an
image) from data content determination engine 104 (FIG. 1A) post
obtaining of data by data obtainer engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one safety setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g., OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate the
display instruction to the data content provider engine 108. If
displayed data needs to be modified to be consistent with at least
one safety setting, the data content provider engine 108 (FIG. 1A)
may transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with child
safety setting such as "display only non-violent data," or "display
only ethnic and gender neutral data."
[0642] Further, the operation 2604 illustrates providing a data
display option of displaying a data portion consistent with a
public safety setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g., data is an
image of format gif) from data content determination engine 104
(FIG. 1A) post obtaining of data by data obtainer engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one desirability setting.
For instance, data content provider engine 108 may receive at least
one display instruction (e.g., OK to display image) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If displayed data needs to be modified
to be consistent with at least one public safety setting, the data
content provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data content provider engine 108 may then
display the data portion consistent with the public safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with
public safety setting such as "display only non-confidential
data."
[0643] FIG. 71 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2702.
[0644] The operation 2702 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one child safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a child safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If displayed
data needs to be modified to be consistent with at least one child
safety setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the child safety setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a child safety setting such as "display
only non-violent data."
[0645] FIG. 72 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 2802.
[0646] Further, the operation 2802 illustrates providing a data
display option of displaying a data portion consistent with a home
safety setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one home safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a home safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If displayed
data needs to be modified to be consistent with at least one home
safety setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the home safety setting. For instance, the data display option
may be displaying on a display of a real machine only a data
portion consistent with home safety setting such as "okay to
display private or confidential data."
[0647] FIG. 73 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3502.
[0648] The operation 2902 illustrates providing a data display
option of displaying a data portion consistent with a workplace
safety setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, and/or 13 may include one or more instruction generating
modules configured to provide an instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a workplace safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If displayed data needs to be
modified to be consistent with at least one workplace safety
setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the workplace safety setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a workplace safety setting such as "display
only non-personal data."
[0649] FIG. 74 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3002, an operation 3004, and/or an
operation 3006.
[0650] The operation 3002 illustrates redirecting to alternative
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108, and an
instruction to provide the data display option of redirecting to
alternative data (e.g., another website). For instance, data
content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data.
[0651] Further, the operation 3004 illustrates automatically
redirecting to alternative data. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination from
data content determination engine 104 (FIG. 1A) post obtaining of
data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of redirecting to alternative
data (e.g., another website) consistent with a user preference. For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate a
redirect to alternative data consistent with the user preference
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with the user preference. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then automatically (e.g., prior to alerting a user) display the
alternative data. For instance, a real machine 130 may be
automatically redirected to an acceptable web link, or a page of
acceptable data.
[0652] Further, the operation 3006 illustrates providing a list of
selectable alternative data options. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post obtaining
of data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
providing a list of selectable alternative data options (e.g., a
list of alternative websites) consistent with a user preference.
For instance, data content provider engine 108 may receive at least
one provide selectable alternatives instruction from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to transmit a provide selectable alternatives instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data content provider engine 108:
The data content provider engine 108 may transmit the provide
selectable alternatives instruction to the--data redirection engine
128 to provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data content provider engine 108.
Data content provider engine 108 may then display the list of
selectable alternatives. For instance, the list of selectable
alternative data options may include a list of acceptable web links
or a selectable list of web pages. Selectable web links and web
pages may include a thumbnail image of the first page of the web
link or of the web page.
[0653] FIG. 75 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3102, and/or an operation 3104.
[0654] The operation 3102 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination (e.g., data does not contain spyware) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
displaying data consistent with at least one privacy related
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g., OK to display webpage) from
at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a privacy related setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one privacy related
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data consistent
with the privacy related setting. For instance, a portion of a
returned webpage including data requesting private user information
such as a user's social security number or e-mail address may be
removed from the web page prior to display of the data on a
computer screen. Further specific examples include a webpage or
website data may be determined to be displayable if the data
satisfies a setting such as a privacy related setting such as a
setting relating to a user's biographical information or financial
information, a webpage or website data may be determined to be
displayable if the data satisfies a group privacy related setting
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting, or a webpage or website data
may be determined to be displayable if the data satisfies a privacy
setting determined by a corporation or other organization to
maintain corporate or organization privacy.
[0655] Further, the operation 3104 illustrates displaying
alternative data consistent with a customized user setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data does not contain
malware) from data content determination engine 104 (FIG. 1A) post
obtaining of data by data obtainer engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
displaying data consistent with at least one user setting. For
instance, data content provider engine 108 may receive at least one
display instruction (e.g., OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may--include one or more instruction generating modules configured
to provide an instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one user setting, the data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108. Data content provider engine 108 may then display the
data consistent with the user setting. Thus, a webpage or website
data may be determined to be displayable if the data satisfies a
user setting when at least one of virtual machines 11, 12, and/or
13 compares the data to the user setting. For instance, a portion
of a webpage produced by a search including non-English text may be
removed from the web page prior to display of the data on a
computer screen. Further, in one specific example, a webpage or
website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[0656] FIG. 76 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3202, and/or an operation 3204.
[0657] The operation 3202 illustrates displaying alternative data
consistent with a desirability setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination (e.g., data is an image) from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer: effect of content
acceptability determination to the data-provider engine 108, and an
instruction to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g., OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
desirability setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one desirability setting, the data content provider engine
108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the desirability
setting. For instance, the data display option may be displaying on
a display of a real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to bee displayable
if the data satisfies an age appropriateness desirability setting
such as a setting based on the Motion Picture of America
Association film rating system.
[0658] Further, the operation 3204 illustrates displaying
alternative data consistent with a workplace established setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data is a social
networking site) from data content determination engine 104 (FIG.
1A) post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one workplace
established setting. For instance, data content provider engine 108
may receive at least one display instruction (e.g., do not display
data) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a workplace
established setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one workplace established setting, the data content provider
engine 108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the workplace
established setting. For instance, the data display option may be
displaying on a display of a real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[0659] FIG. 77 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3302.
[0660] The operation 3302 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a user
history setting (e.g., another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user history setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a user history setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a user history setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. For instance, displayed
alternative data may be consistent with a user history such as
having viewed only music related data and pages.
[0661] FIG. 78 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3402, an operation 3404, and/or an
operation 3406.
[0662] The operation 3402 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post obtaining
of data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
redirecting to alternative data consistent with a safety setting
(e.g., another website). For instance, data content provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide a redirect instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a safety setting stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a safety setting instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the redirect data instruction to the data redirection
engine 128 for redirection to alternative data consistent with a
safety setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a safety setting may
include displaying a different webpage including only information
consistent with a safety setting such as "do not display links
requesting credit card information."
[0663] Further, the operation 3404 illustrates displaying
alternative data consistent with a public safety setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102--(FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108, and an
instruction to provide the data display option of redirecting to
alternative data consistent with a public safety setting (e.g.,
another website). For instance, data content provider engine 108
may receive at least one redirect instruction from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide a redirect instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a public safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a public safety setting instruction to the data
content provider engine 108. The data content provider engine 108
may transmit the redirect data instruction to the data redirection
engine 128 for redirection to alternative data consistent with a
public safety setting. The data redirection engine 128 may transmit
the redirection to the data content provider engine 108. Data
content provider engine 108 may then display the alternative
data.
[0664] Displaying alternative data consistent with a public safety
setting may include displaying a different webpage including only
information consistent with a public safety setting such as
"display only non-confidential data." Public safety setting may
include a transmittable information safety setting, a viewable
information safety setting and a receivable information safety
setting. Transmittable or viewable information may be private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information.
Receivable information may be any information such as text, images,
a virus, spyware, or any other information that a user's real
machine may be capable of receiving from an external source.
[0665] The operation 3406 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A). may--be in communication
with Effect of content acceptability: determination engine 106
(FIG. 1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a home
safety setting (e.g., another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a home safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a home safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a home safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a home safety setting may include displaying a
different webpage including only information consistent with a home
safety setting such as "do not display links requesting address
information."
[0666] FIG. 79 illustrates alternative embodiments of the example
operational flow 200B of FIG. 46 where the operation 240B may
include at least one additional operation. Additional operations
may include an operation 3502, and/or an operation 3504.
[0667] The operation 3502 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a
workplace safety setting (e.g., another website). For instance,
data content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the redirect to alternative data consistent with a
workplace safety setting instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a workplace safety
setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a workplace safety
setting may include displaying a different webpage including only
information consistent with a workplace safety setting such as "do
not display links requesting information on this computer."
[0668] Further, the operation 3504 illustrates displaying
alternative data consistent with a child safety setting. Continuing
the example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post obtaining of data by data obtainer engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g., another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a child safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a child safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a child safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a child safety setting may include displaying a
different webpage including only information consistent with a
child safety setting such as "do not display links containing
trailers for rated `R` movies."
Application Ser. No. 12/005,637 (1206-003-007A2-000002)
[0669] Referring to FIG. 80, after a start operation, the
operational flow 200 moves to an operation 210. Operation 210
illustrates obtaining at least a portion of data from a data source
(e.g., a server accessible from the internet). For example, FIG. 1A
illustrates a data obtainer engine 102. Data obtainer engine may
obtain (e.g., download) data 110 (e.g., a web page) from a data
source such as a computer accessible from the internet.
[0670] Specifically, data 110 may be web content obtained from the
World Wide Web via a computing device accessible from the Internet.
For example, data obtainer engine 102 may set a URL and add a query
string value to the URL. Data obtainer engine 102 may then make a
request to the URL and scan the response received from the URL.
Data 110 may be a web site or web page containing one or more links
to additional web sites, such as shown, for example, in FIG. 1B
and/or FIG. 1C. Data 110 may in some instances be textual, a
two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content. Data obtainer engine 102 may transmit at least a
portion of obtained data to data content determination engine
104.
[0671] Then, operation 220 illustrates determining a content of the
data (e.g., detecting if an image in a link is in jpeg format).
Continuing the example above, FIG. 1A illustrates a data content
determination engine 104. Data content determination engine 104 may
determine the content (e.g., a format/protocol) of at least a
portion of the data 110 obtained from the data source by the data
obtainer engine 102. Data content determination engine 104 may
isolate (e.g., quarantine) at least a portion of the data 110 prior
to determining data content (e.g., video is a Real Networks video).
Data content determination engine 104 may utilize, for example,
pointers or other file format identifiers to determine data
content. For example, data content determination engine 104 may
locate a format specification document within the data content to
determine how data 110 is encoded or determine a format of a data
content by determining a filename extension (e.g., .htm, .gif,
.wav) for the data content or a file format identifier (e.g.,
identifying a file format according to origin and file category)
for the data content. Data content determination engine 104 may
provide Effect of content acceptability determination engine 106
with determined data content information to assist Effect of
content acceptability determination engine 106 to determine an
effect of the content. Data content formats may be any text, image,
audio, and/or video file formats including, but not limited to JPEG
format, or other format designed to store static photographic
images, GIF format, or other format supporting storage of both
still images and/or animations, QuickTime format, Windows Media
Player format, or other format configured to store multiple
multimedia formats.
[0672] Then, operation 230 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least two virtual machine representations operating
at least in part on an individual core of a multi-core system
(e.g., a multi-core processor, a multi-core system on a chip,
etc.). Continuing the example above, Effect of content
acceptability determination engine 106 (FIG. 1A) may receive data
and an associated data content determination (e.g., data content is
a Windows Media Audio format audio file) from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and transfer of obtained data to data content
determination engine 106. Data content determination engine may
provide Effect of content acceptability determination engine 106
with information regarding a format/protocol of content at least a
portion of the data. Effect of content acceptability determination
engine 106 may utilize format/protocol information to determine
whether Effect of content acceptability determination engine should
call a specific database or library (e.g., a Windows Media Player
library) to obtain file format information. File format information
may be utilized to compare received data content to data stored in
a library. Effect of content acceptability determination engine 106
(FIG. 1A) may utilize, for example, virtual machine 12 (FIG. 1A)
spawned by virtual machine module 118 on an individual core of a
multi-core system to determine whether data associated with Link 2
would result in a change in the operating system of real machine
130 contra to user preferences regarding the operating system as
reflected by user preference database 120.
[0673] Then, operation 240 illustrates displaying at least one data
display option based on the determining an acceptability of a
content of the data. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
transfer at least one effect of content acceptability determination
(e.g., content contains malware) to the data content provider
engine 108. Data content provider engine 108 may provide at least
one data display option (e.g., displaying a message that content
will not display) to a user based on the received effect of content
acceptability determination. In one example, data provider engine
108 provides data via placing the data on a visual display, where
the content is such that it meets one or more thresholds associated
with the effect of content acceptability determination 106.
Provided data may be a list of web links, a web page, or other data
that either have been deemed acceptable by effect of content
acceptability determination engine 106 or that have been modified
(e.g., obfuscated), such as by data modification engine 122, such
that the to-be-displayed content is judged acceptable under user
preferences. Provided data may be modified via the data
modification engine 122. For instance, provided data may be
obfuscated via the data obfuscation engine 124 (e.g., at least a
portion of the displayed data may be blurred out or disabled), or
provided data may be anonymized via the data anonymization engine
126 (e.g., at least a portion of the data may be deleted entirely).
Data content provider engine 108 (FIG. 1A) may receive at least one
display instruction (e.g., OK to display links 1 and 2) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A) for at least a portion of data
to be displayed. For instance, at least one of virtual machines 11,
12, and/or 13 may include one or more instruction generating
modules configured to provide an instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Such instruction may include an
instruction to the data content provider engine 108 to prevent the
data content provider engine 108 from displaying data that may
configure a hardware profile of real machine 130 counter to
anti-viral settings stored in the user preference database 120
(FIG. 1A), or an instruction to the data content provider engine
108 to prevent the data content provider engine 108 from displaying
data that may configure an operating system of real machine 130
counter to a previous operating system of the real machine 130
(e.g., determine if a rootkit has been installed).
[0674] FIG. 81 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[0675] The operation 302 illustrates examining a database of known
content for data content information. Continuing the example above,
data content determination engine 104 (FIG. 1A) may transmit at
least a portion of data content to a database examination engine
112 to extract data content information from at least a portion of
the data. A database examination engine 112 may examine (e.g.,
scan) a database (e.g., information obtained from a storage server)
of known data (e.g., a database of known audio formats) and compare
the known data to the data 110 to determine data content (e.g.,
audio content is in mp3 format). Data content determination may be
transmitted from the database examination engine 112 to the data
content determination engine 104, and the data content
determination engine 104 may subsequently transmit the data content
determination to the Effect of content acceptability determination
engine 106. Database examination engine 112 may be configured to
examine a database of data provided, for example, by a data
provider service or a database of data stored on a real machine
130. For instance, a database may include a list of links viewed by
a user or pre-approved by a user based on one or more
user-specified preferences, such as links from a specific source of
information (e.g., the Roman Catholic Church).
[0676] The operation 304 illustrates traversing at least a portion
of the data in real time. Continuing the example above, data
content determination engine 104 (FIG. 1A) may transmit at least a
portion of data content to a data transverser engine 114 to extract
data content information from at least a portion of the data. A
data transverser engine 114 may traverse (e.g., parse) at least a
portion of the data (e.g., a portion of a web page) to determine a
format for at least a portion of data content (e.g., an image
format or video format) within the portion of the data. Data
traversal may occur in real time (e.g., simultaneously as data is
loading). Data content determination may be transmitted from the
data transverser engine 114 to the data content determination
engine 104, and the data content determination engine 104 may
subsequently transmit the data content determination to the Effect
of content acceptability determination engine 106.
[0677] The operation 306 illustrates locally examining at least a
portion of the data. Continuing the example above, data content
determination engine 104 may transmit at least a portion of data
content to a local data examination engine 116 (FIG. 1A) to extract
data content information from at least a portion of the data. A
local data examination engine 116 may locally (e.g., on the real
machine 130) examine (e.g., analyze) at least a portion of the data
(e.g., one or more pointers in the data) to determine data content
(e.g., an audio file is a .wav file). For instance, local data
examination engine 116 may view an amount of html source code to
locate markers signifying the format of at least a portion of data
content. Data content determination may be transmitted from the
local data examination engine 116 to the data content determination
engine 104. Data content determination engine 104 may transmit a
data content determination to the Effect of content acceptability
determination engine 106.
[0678] FIG. 82 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, and/or an operation
406.
[0679] The operation 402 illustrates examining at least a portion
of the data to locate references to additional content. Continuing
the example above, Effect of content acceptability determination
engine 106 (FIG. 1A) may receive a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, and/or 13 (FIG. 1B). Each of
virtual machines 11, 12, and/or 13 may examine (e.g., scan) at
least a portion of data (e.g., an imbedded link on a webpage) to
determine if the data references additional content (e.g., one or
more additional images). Additional content may be a web page
comprising text and/or an image, a link to a web page, a video or
any combination of text, images, links to web pages, or videos.
Virtual machines 11, 12, and/or 13 may traverse additional data to
determine an acceptability of an effect of the data content. Effect
of content acceptability determination may be communicated to
Effect of content acceptability determination engine 106 (FIG. 1A)
that may communicate an effect of content acceptability
determination to a data provider engine 108 (FIG. 1A).
[0680] The operation 404 illustrates determining whether the data
references additional data content information when loading.
Continuing the example above, Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post obtaining of data
by data obtainer engine 102 and communication of obtained data to
data content determination engine 104. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. Any of virtual machines 11, 12, and/or 13 may examine the data
in real time as it loads onto the virtual machine 11, 12, and/or 13
to determine if the data (e.g., Link 1) references additional data
(e.g., Link 4) when loading. For instance, if a link to a webpage
immediately (e.g., as soon as the link is activated) references an
additional link (e.g., to redirect a user), a virtual machine 11,
12, and/or 13 may determine that such a reference to an additional
link has been made. Virtual machines 11, 12, and/or 13 may
determine whether data references additional data at any time when
the data is loading. Effect of content acceptability determination
engine 106 (FIG. 1A) may communicate an effect of content
acceptability determination to a data provider engine 108 (FIG.
1A).
[0681] The operation 406 illustrates issuing a request to a remote
computer for additional data content information. Continuing the
example above, Effect of content acceptability determination engine
106 (FIG. 1A) may receive a data content determination from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 on at
least one core of a multi-core system including, for example, cores
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or 13
(FIG. 1B). Each of virtual machines 11, 12, and/or 13 may examine
(e.g., scan) at least a portion of data (e.g., an imbedded ink on a
webpage) to determine if the data references additional data (e.g.,
one or more additional links). Additional data may be a web page
comprising text and/or an image, a link to a web page, a video or
any combination of text, images, links to web pages, or videos.
Virtual machines 11, 12, and/or 13 may traverse additional data to
determine an acceptability of an effect of the data content. Effect
of content acceptability determination may be communicated to
Effect of content acceptability determination engine 106 (FIG. 1A)
that may communicate an effect of content acceptability
determination to a data provider engine 108 (FIG. 1A).
[0682] FIG. 83 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 502, and/or an operation 504.
[0683] The operation 502 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least two virtual machine representations operating
at least in part on an individual core of a multi-core system at
least partially resident within a real machine Continuing the
example above, Effect of content acceptability determination engine
106 (FIG. 1A) may receive a data content determination from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, and/or 13. In one
implementation, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may be generated on the real machine 130 (e.g., as a
subsystem of real machine 130).
[0684] The operation 504 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least two virtual machine representations operating
at least in part on an individual core of a multi-core system at
least partially non-resident within a real machine. Continuing the
example above, Effect of content acceptability determination engine
106 (FIG. 1A) may receive a data content determination from data
content determination engine 104 post obtaining of data by data
obtainer engine 102 and communication of obtained data to data
content determination engine 104. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118 including virtual machines 11, 12,
and 13. In one implementation, at least one of virtual machines 11,
12, and/or 13 may be generated on a remote server, remote operating
system or otherwise geographically distinct location with respect
to the real machine 130.
[0685] FIG. 84 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 602, and/or an operation 604.
[0686] The operation 602 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of
content of a real machine. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102. Effect of content acceptability determination engine
106 may transfer data received from data content determination
engine 104 following a determination of data content. Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to the virtual
machine module 118. Virtual machine module 118 (FIG. 1A) may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
further illustrates virtual machines 11, 12, and 13 including a
virtual machine representation of content of the real machine 130
post activation of Link 1, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
email, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation may include determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine include determining whether or not a video or image
has been loaded onto, for example, the virtual machine 11 after
loading at least a portion of the data contained in Link 1.
[0687] The operation 604 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of
software of a real machine. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102. Effect of content acceptability determination engine
106 may transfer data received from data content determination
engine 104 following a determination of data content. Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to the virtual
machine module 118. Virtual machine module 118 (FIG. 1A) may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software, such as a
state of Windows Media Player) of the real machine 130 post (e.g.,
subsequent to) activation of Link 1. Examples of such software
might include a commercial word processing program or suite of
programs (e.g., Microsoft.RTM. Office for Windows), an open source
Web browser (e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up
(e.g., an executing JavaScript.TM. and/or data obtained by same via
an XML-like scheme), a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware program (e.g., such as those of Symantec
Corporation or McAfee, Inc.), a multi-media program (e.g.,
QuickTime) etc. An example of determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation may include determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine include determining whether or not an unauthorized
program or suite of programs (e.g., music downloading software) has
been loaded, for example, onto virtual machine 12 after loading at
least a portion of the data contained in Link 2.
[0688] FIG. 85 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 702, and/or an operation 704.
[0689] The operation 702 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of
hardware of a real machine. Continuing the example above, Effect of
content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and may transfer data received from data content
determination engine 104 following a determination of data content.
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to the
virtual machine module 118. FIG. 1B illustrates virtual machine 11
including a virtual machine representation of hardware (e.g., a
state of the hardware) of the real machine 130 post activation of
Link 1. Examples of such hardware might include all or part of a
chipset (e.g., data processor and/or graphics processor chipsets
such as those of Intel Corporation and/or NvidiaCorporation), a
memory chip (e.g., flash memory and/or random access memories such
as those of Sandisk Corporation and/or Samsung Electronics, Co.,
LTD), a data bus, a hard disk (e.g., such as those of Seagate
Technology, LLC), a network adapter (e.g., wireless and/or wired
LAN adapters such as those of Linksys and/or CiscoTechnology,
Inc.), printer, a removable drive (e.g., flash drive), a cell
phone, etc. An example of determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of the hardware of the real
machine includes determining whether a network adapter on, for
example, virtual machine 12 has been disabled after loading at
least a portion of the data contained in Link 2.
[0690] The operation 704 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of at least a portion of an
operating system of a real machine. Continuing the example above,
Effect of content acceptability determination engine 106 (FIG. 1A)
may receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102. Effect of content acceptability determination engine
106 may transfer data received from data content determination
engine 104 following a determination of data content. Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to the virtual
machine module 118. Virtual machine module 118 (FIG. 1A) may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had link 1, link 2,
and/or link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of an operating system (e.g., a state of an
operating system and/or network operating system) of the real
machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or a network
operating system (e.g., the Internet Operating System available
from Cisco Technology, Inc. Netware.RTM. available from Novell,
Inc., and/or Solaris available from Sun Microsystems, Inc.). An
example of determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of an operating system of the real machine
include determining whether a portion of the operating system
(e.g., Microsoft Vista) on for example, virtual machine 12 has been
disabled after loading at least a portion of the data contained in
Link 2.
[0691] FIG. 86 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 802, an operation 804, and/or an operation
806.
[0692] The operation 802 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of a real machine including at
least a portion of a computing device. FIG. 1D illustrates real
machine 130 including at least a part of a computing device 132.
The computing device 132 may be any device capable of processing
one or more programming instructions. For example, the computing
device 132 may be a desktop computer, a laptop computer, a notebook
computer, a mobile phone, a personal digital assistant (PDA),
combinations thereof, and/or other suitable computing devices.
[0693] The operation 804 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
two virtual machine representations of a real machine including at
least one peripheral device. Continuing the example above, Effect
of content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and communication of obtained data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 may spawn at least one of virtual
machines 11, 12, and/or 13 that may be a virtual machine
representation of at least a part of real machine 130. Real machine
130 (FIG. 1B) may include at least one peripheral device. For
instance, FIG. 1D illustrates real machine 130 including at least
one peripheral device 134-146. FIG. 1D illustrates a representative
view of an implementation of real machine 130 (e.g., a desktop,
notebook, or other type computing system, and/or one or more
peripheral devices) in which all/part of system 100 may be
implemented. FIG. 1D illustrates that implementations of real
machine 130 may include all/part of computing device 132 and/or
all/part of one or one or more peripherals associated computing
device 132.
[0694] Further, the operation 806 illustrates determining an
acceptability of an effect of content of the data at least in part
via at least two virtual machine representations of a real machine
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, Effect
of content acceptability determination engine 106 (FIG. 1A) may
receive a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102 and communication of obtained data to data content
determination engine 104. Virtual machine module 118 (FIG. 1A) may
spawn at least one of virtual machines 11, 12, and/or 13 that may
be a virtual machine representation of at least a part of real
machine 130. Real machine 130 may include at least one peripheral
device. For instance, FIG. 1D illustrates a real machine may also
include at least a portion of one or more peripheral devices
connected/connectable (e.g., via wired, waveguide, or wireless
connections) to real machine 130. Peripheral devices may include
one or more printers 134, one or more fax machines 136, one or more
peripheral memory devices 138 (e.g., flash drive, memory stick),
one or more network adapters 139 (e.g., wired or wireless network
adapters), one or more music players 140, one or more cellular
telephones 142, one or more data acquisition devices 144 (e.g.,
robots) and/or one or more device actuators 146 (e.g., an hydraulic
arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
[0695] FIG. 87 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 902, and/or an operation 904.
[0696] The operation 902 illustrates determining a state of at
least one of the at least two virtual machine representations
operating at least in part on an individual core of a multi-core
system prior to loading at least a portion of the data. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106 including a virtual machine
module 118, further including at least one of virtual machines 11,
12, and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post obtaining of data
by data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may determine a state of at least one component (e.g., the
hardware) of the virtual machine prior to activation (e.g., before)
of a link. Virtual machine state may be representative of a state
for all or at least a portion of the components (e.g., content,
software, hardware, operating system) of the real machine 130
represented by the virtual machine 11, 12, and/or 13. For instance,
at least one of virtual machines 11, 12, and/or 13 may be
determined to be free of viruses, an amount of virtual machine
memory may be measured, or a processing speed of at least one of
virtual machines 11, 12, and/or 13 may be determined. At least one
of virtual machines 11, 12, and/or 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[0697] The operation 904 illustrates determining a state of at
least one of the at least two virtual machine representations
operating at least in part on an individual core of a multi-core
system subsequent to loading at least a portion of the data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12,
and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post obtaining of data
by data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may determine a state of at least one component (e.g., the
hardware) of the virtual machine subsequent to (e.g., after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by at least one of virtual machines 11, 12, and/or 13
after at least a portion of the data has loaded. For instance, at
least one of virtual machines 11, 12, and/or 13 may be determined
to contain a virus, an amount of virtual machine memory may be
measured, or a processing speed of at least one of virtual machines
11, 12, and/or 13 may be determined. At least one of virtual
machines 11, 12, and/or 13 may be examined to determine, for
example, if a virus or any other undesired software is present on
the machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[0698] FIG. 88 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1002, and/or an operation 1004.
[0699] The operation 1002 illustrates determining a state change of
at least one of the at least two virtual machine representations
operating at least in part on an individual core of a multi-core
system between a prior state and a subsequent state of at least one
of the at least two virtual machine representations operating at
least in part on an individual core of a system comprising at least
two cores after loading at least a portion of the data. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106 including a virtual machine
module 118 further including virtual machines 11, 12, 13. Upon
receiving data and a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. A state change (e.g., a
decrease in memory) of at least one of virtual machines 11, 12,
and/or 13 (FIG. 1B) may be determined by a component of at least
one of virtual machines 11, 12, and/or 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[0700] Further, the operation 1004 illustrates determining whether
a state change on at least one of the at least two virtual machine
representations operating at least in part on an individual core of
a multi-core system is an undesirable state change based on one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer the data
and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. An undesirable state change may
be determined by examining the changes to at least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) and comparing the state change
of at least one of virtual machines 11, 12, and/or 13 to user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. 1A)
onto at least one of virtual machines 11, 12, and/or 13. A state
change may include any undesirable state changes such as a decrease
in memory or processing speed and/or the presence of a virus or
other undesirable software after at least a portion of the data has
loaded. Undesirable state changes may further include an
undesirable transfer of information located on at least one of
virtual machines 11, 12, and/or 13 to an external location, an
undesirable transfer of data onto at least one of virtual machines
11, 12, and/or 13 from an external location after at least a
portion of the data has loaded on at least one of virtual machines
11, 12, and/or 13 that may result in an undesired change in the
state of content, software, hardware or an operating system of the
real machine 130 and/or an undesirable transfer of data onto at
least one of virtual machines 11, 12, and/or 13 where at least a
portion of the transferred data may be found objectionable when
viewed by a user 10.
[0701] FIG. 89 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1102, an operation 1104, and/or an
operation 1106.
[0702] The operation 1102 illustrates determining an acceptability
of an effect of content of the data in response to at least one
user setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. An acceptability of an effect of content of the data may be
determined by determining if a state change to at least one of
virtual machines 11, 12, and/or 13 has occurred and comparing the
state change of at least one of virtual machines 11, 12, and/or 13
to user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Comparison may be made, for
example by transferring user preference database information from
the user preference database 120 (FIG. 1A) to the virtual machine
module 118 (FIG. 1A) which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one end-user specified preference relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. At least one of virtual machines 11,
12, and/or 13 may determine an acceptability of an effect of the
content of the data based on at least one user setting contained in
a user preference database at least a portion of which may be
spawned onto at least one of virtual machines 11, 12, and/or 13 via
virtual machine module 118 (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a setting established by a user such as a political or
cultural preference setting). Further examples of user preferences
include specific religion or lifestyle preference, such as "return
only links relating to Roman Catholicism" or "return only links
relating to a vegan lifestyle" that may be stored in the real
machine 130. User-specific preference may also relate to user
information safety or computer safety, such as "do not display
links requesting information from my computer," or "do not display
links that transfer viruses onto my computer."
[0703] Further, the operation 1104 illustrates determining an
acceptability of an effect of content of the data in response to a
personal user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a personal user
setting (e.g., "show only automobile related data") contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one personal user setting relating to at least
one of content, software, hardware and/or an operating system of a
real machine 130. Personal user setting may be a setting input by a
user that is personal to the user, such as an information security
level, a content filter level, or a personal desirability setting
such as "show only non-religious data" or "show only automobile
related data."
[0704] Further, the operation 1106 illustrates determining an
acceptability of an effect of content of the data in response to a
peer user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, and 13. Upon receiving data and a data
content determination from data content determination engine 104
post obtaining of data by data obtainer engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12, and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
at least one of virtual machines 11, 12, and/or 13. At least one of
virtual machines 11, 12, and/or 13 may compare the data received
from the virtual machine module to a peer user setting contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one peer user setting relating to at least one
of content, software, hardware and/or an operating system of a real
machine 130. Peer user setting may be a setting input by a user
that is determined by a peer group, such as a peer group determined
information security level such as "display only 100 percent secure
websites", a peer group determined data filter level such as
"filter 100% of obscene data", or a peer group desirability setting
such as "show only classical music related data" or "show only
knitting related data."
[0705] FIG. 90 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1202, and/or an operation 1204.
[0706] The operation 1202 illustrates determining an acceptability
of an effect of content of the data in response to a corporate user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a corporate user
setting contained in user preference database information spawned
on at least one of virtual machines 11, 12, and/or 13. User
preference database 120 may include at least one corporate user
setting relating to at least one of content, software, hardware
and/or an operating system of a real machine 130. Corporate user
setting may be a setting input by a corporation that is determined
to the corporation, such as a corporate desirability setting such
as "show only real-estate related data" or "show only agricultural
related data."
[0707] The operation 1204 illustrates determining an acceptability
of an effect of content of the data in response to a work safety
user setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a work safety user
setting contained in user preference database information spawned
on at least one of virtual machines 11, 12, and/or 13. User
preference database 120 may include at least one work safety user
setting relating to at least one of content, software, hardware
and/or an operating system of a real machine 130. Thus, in one
specific example, a webpage or website data may be determined to be
displayable if the data satisfies a work safety user setting such
as a corporate information security level, corporate user setting,
or a corporate information content filter level corporate user
setting.
[0708] FIG. 91 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1302, an operation 1304, and/or an
operation 1306.
[0709] The operation 1302 illustrates determining an acceptability
of an effect of content of the data in response to a desirability
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a desirability
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a desirability
setting established by a user such as a desire to view only
non-obscene material) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. User preference database 120 may include at least one
desirability setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130.
[0710] Further, the operation 1304 illustrates determining an
acceptability of an effect of content of the data in response to a
religious desirability setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 may compare the data received from the
virtual machine module 118 to a religious desirability setting
(e.g., does a website contain only images, text, audio or visual
data suitable for viewing by a user based on a religious
desirability setting established by a user such as a desire to view
only Hindu material) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A religious desirability setting may be include any
setting regarding a major, minor, or other religion such as
Christianity, Judaism, Islam, Hinduism, and so on.
[0711] Further, the operation 1306 illustrates determining an
acceptability of an effect of content of the data in response to a
political desirability setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a political
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a political desirability setting established by a user such as a
desire to view only Democratic Party material) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A political desirability setting may
include any setting regarding a political party or affiliation
(e.g., Republican, Democratic, Libertarian, Green Party, etc.).
[0712] FIG. 92 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1402, and/or an operation 1404.
[0713] The operation 1402 illustrates determining an acceptability
of an effect of content of the data in response to a cultural
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a cultural
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a cultural desirability setting established by a user such as a
desire to view only materials regarding early Mayan civilization)
contained in user preference database information spawned on at
least one of virtual machines 11, 12, and/or 13. A cultural
desirability setting may include any culturally related information
such as a religious, ethnic, regional, or heritage based cultural
desirability setting or any other cultural desirability
setting.
[0714] Further, the operation 1404 illustrates determining an
acceptability of an effect of content of the data in response to a
theme related desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, and/or 13. User preference database information
stored in the user preference database 120 (FIG. 1A) may be
transferred to the virtual machine module 118 (FIG. 1A), which
spawns a copy of at least a portion of the user preference database
120 (FIG. 1A) onto at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a theme related desirability setting (e.g., does a
website contain only images, text, audio or visual data suitable
for viewing by a user based on a theme related desirability setting
established by a user such as a desire to view only materials
regarding collectible stamps) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A theme related desirability setting may include any
theme related information, such as information relating to cars,
fashion, electronics, sports, hobbies, collector's items, or any
theme or category that may be of interest to a user.
[0715] FIG. 93 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1502.
[0716] The operation 1502 illustrates determining an acceptability
of an effect of content of the data in response to an age
appropriateness desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, and/or 13. User preference database information
stored in the user preference database 120 (FIG. 1A) may be
transferred to the virtual machine module 118 (FIG. 1A), which
spawns a copy of at least a portion of the user preference database
120 (FIG. 1A) onto at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to an age appropriateness desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on an age appropriateness
desirability setting established by a user such as a desire to view
only materials given a PG or lower rating as determined by the
Motion Picture of America Association film rating system) contained
in user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. An age appropriateness
desirability setting may include any age appropriate setting, such
as a rating threshold or a profanity threshold.
[0717] FIG. 94 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1602, an operation 1604, and/or an
operation 1606.
[0718] The operation 1602 illustrates determining an acceptability
of an effect of content of the data in response to at least one
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a privacy related
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a privacy
related setting established by a user) contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. A privacy related setting may include any
privacy related settings (e.g., does a website contain only data
that will not request information from my computer or allow others
to view personal information saved on my computer).
[0719] Further, the operation 1604 illustrates determining an
acceptability of an effect of content of the data in response to a
user specific privacy related setting. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post obtaining of data by data obtainer engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, and/or 13. User preference database information
stored in the user preference database 120 (FIG. 1A) may be
transferred to the virtual machine module 118 (FIG. 1A), which
spawns a copy of at least a portion of the user preference database
120 (FIG. 1A) onto at least one of virtual machines 11, 12, and/or
13. At least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a user specific privacy related setting (e.g., will a
website request specific information about the user such as name,
address, telephone number) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A user specific privacy related setting may include any
user specific privacy related settings (e.g., a setting relating to
a user's biographical information or financial information).
[0720] Further, the operation 1606 illustrates determining an
acceptability of an effect of content of the data in response to a
group privacy related setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a group privacy
related setting (e.g., will a website request information about an
organization such as name, address, telephone number) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. A group privacy related setting
may include any group privacy related settings (e.g., a setting
relating to a group's membership). Group privacy related setting
may be any setting established by a group such as a work group
(e.g., employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g., members of family unit)
privacy related setting.
[0721] FIG. 95 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1702, and/or an operation 1704.
[0722] The operation 1702 illustrates determining an acceptability
of an effect of content of the data in response to a corporate
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to a corporate
privacy related setting (e.g., will a website request information
about a corporation such as data stored on a real machine belonging
to the corporation) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Corporate privacy related setting may be determined by a
corporate issued privacy manual, or other such document or mandate
set forth by officers of a corporation.
[0723] Further, the operation 1704 illustrates determining an
acceptability of an effect of content of the data in response to
transmitted user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to at least one
acceptable type of transmitted user information setting (e.g., do
not return links that will transmit my e-mail address, home address
or telephone number to an external location) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. Acceptable type of transmitted user
information setting may be determined by a user 10 (FIG. 1B). For
instance, acceptability of the effect of the data may be determined
in response to whether or not private user information, such as
credit card numbers, bank accounts, personal identification
information or any other personal user information may be
transmitted to a location external to the real machine by selecting
the link.
[0724] FIG. 96 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1802, and/or an operation 1804.
[0725] The operation 1802 illustrates determining an acceptability
of an effect of content of the data in response to captured user
information. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post obtaining of data by
data obtainer engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, and/or
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to at least one
acceptable type of captured user information setting (e.g., do not
return links that will capture my e-mail address, home address or
telephone number) contained in user preference database information
spawned on at least one of virtual machines 11, 12, and/or 13.
Acceptable type of captured user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be captured by a machine located at a location
external to the real machine by selecting the link.
[0726] Further, the operation 1804 illustrates determining an
acceptability of an effect of content of the data in response to
exposed user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto at least
one of virtual machines 11, 12, and/or 13. At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may compare the data received
from the virtual machine module 118 (FIG. 1A) to at least one
acceptable type of exposed user information setting (e.g., do not
return links that will expose personal financial information stored
on the real machine 130) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Acceptable types of exposed user information settings
may be determined by a user 10 (FIG. 1B). For instance,
acceptability of the effect of the data may be determined in
response to whether or not private user information, such as credit
card numbers, bank accounts, personal identification information or
any other personal user information may be exposed to a machine
located at a location external to the real machine by selecting the
link.
[0727] FIG. 97 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 1902, and/or an operation 1904.
[0728] The operation 1902 illustrates determining an acceptability
of an effect of content of the data in response to visually
examining at least a portion of a data image on at least one of the
at least two virtual machine representations operating at least in
part on an individual core of a multi-core system. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106 including a virtual machine
module 118 further including virtual machines 11, 12, 13. Upon
receiving data and a data content determination from data content
determination engine 104 post obtaining of data by data obtainer
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12, and/or 13. To visually examine a data
image, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may include an image scanning module. Visually examining the data
image may include, for example, color analysis, pattern-matching,
pattern-recognition, or any other technique for recognizing a
particular image or type of image.
[0729] The operation 1904 illustrates determining an acceptability
of an effect of content of the data at least in part via at least
three virtual machine representations of at least a part of a real
machine having at least one end-user specified preference, at least
one of the at least three virtual machine representations operating
at least in part on an individual core of a multi-core system
comprising at least three cores (i.e. chip-level multiprocessor).
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118, further including virtual machines 11, 12,
and/or 13 operating on Cores 11, 12, and/or 13, respectively of a
multi-core system. Upon receiving data and a data content
determination from data content determination engine 104 post
obtaining of data by data obtainer engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data and associated data
content determination to at least one of virtual machines 11, 12,
and/or 13. At least one of virtual machines 11, 12, and/or 13 may
determine a state of at least one component (e.g., the hardware) of
the virtual machine prior to activation (e.g., before) of a link.
Virtual machine state may be representative of a state for all or
at least a portion of the components (e.g., content, software,
hardware, operating system) of the real machine 130 represented by
the virtual machine 11, 12, and/or 13. Multi-core system may
include at least one additional core, such as, for instance, Core
31 (FIG. 1C), Core 32 (FIG. 1C) and/or Core 33 (FIG. 1C).
[0730] FIG. 98 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2002, and/or an operation 2004.
[0731] The operation 2002 illustrates providing a data display
option of displaying at least a portion of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g., data is a video file) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying at least a portion
of the data. For instance, data content provider engine 108 may
receive at least one display instruction (e.g., OK to display the
entire text of link 1) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. Data content
provider engine 108 may then display the data. Displayed data may
be an unmodified web page of text, images and/or video, or a web
page including links to additional web pages and may be displayed
on a real machine display such as a computer screen.
[0732] The operation 2004 illustrates providing a data display
option of not displaying at least a portion of the data. Continuing
the example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g., data is a video file) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of not displaying at least a
portion of the data. For instance, data content provider engine 108
may receive at least one do not display instruction (e.g., Do not
display the text of link 1) from at least one component of Effect
of content acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
include one or more instruction generating modules configured to
provide a do not display instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the do not display instruction to the
data content provider engine 108. The data display option of not
displaying the data may include a message indicated why the data is
not being displayed, or may be, for example, a blank page displayed
on a display of the real machine.
[0733] FIG. 99 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2102, an operation 2104, and/or an
operation 2106.
[0734] The operation 2102 illustrates providing a data display
option of displaying a modified version of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g., data is a video file) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying at least a portion
of the data. For instance, data content provider engine 108 (FIG.
1A) may receive at least one modify data instruction (e.g., display
only lines 1-10 of the text of link 1) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide a
modify data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the modify data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
may transmit the modified data to the data content provider engine
108. Data content provider engine 108 may then display the modified
version of the data. Displayed data may be a modified web page of
text, a modified image and/or a modified video, or a modified web
page including links to additional web pages. For instance, a
webpage or website may be displaying, but any obscenities on the
web page or website may replaced by non-obscene word
alternatives.
[0735] Further, the operation 2104 illustrates providing a data
display option of obfuscating an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data is a video file)
from data content determination engine 104 (FIG. 1A) post obtaining
of data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of obfuscating (e.g., blurring)
a portion of the data (e.g., obscene photos). For instance, data
content provider engine 108 may receive at least one obfuscate data
instruction (e.g., display only non-obscene portions of the image
in link 1) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 (FIG. 1B) may include one or
more instruction generating modules configured to provide an
obfuscate data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the obfuscate data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the obfuscate data instruction to the data modification
engine 122 which may transmit the obfuscate data instruction to the
data obfuscation engine 124. Data obfuscation engine 124 may
transmit the obfuscated data to the data modification engine 122
for transmission to the data content provider engine 108. Data
content provider engine 108 may then display the obfuscated version
of the data. For example, obfuscating logic may obfuscate
restricted data or imagery within a webpage or image. Obfuscation
may include blurring or blocking of the objectionable data
portion.
[0736] Further, the operation 2106 illustrates providing a data
display option of anonymizing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data entails a video
file of wmv format) from data content determination engine 104
(FIG. 1A) post obtaining of data by data obtainer engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination and an
instruction to the data provider engine 108 to provide the data
display option of anonymizing (e.g., obscuring source information)
for a portion of the data (e.g., graphic videos). For instance,
data content provider engine 108 may receive at least one anonymize
data instruction (e.g., obscure source information for portions of
the video in link 1) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an anonymize
data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the anonymize data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the anonymize data instruction to the data modification
engine 122 which may transmit the anonymize data instruction to the
data anonymization engine 126. Data anonymization engine 126 may
transmit the anonymized data to the data modification engine 122
for transmission to the data content provider engine 108. Data
content provider engine 108 may then display the anonymized version
of the data. Anonymized data may be data in which the original
identity information of the data is hidden, obscured, replaced,
and/or otherwise modified.
[0737] FIG. 100 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2202.
[0738] The operation 2202 illustrates providing a data display
option of at least one of removing, altering or replacing an
objectionable data portion. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination
(e.g., data entails an audio file of MP3 format) from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination and an instruction to the data provider
engine 108 to provide the data display option of removing, altering
or replacing an objectionable data portion (e.g., replacing
profanity with innocuous language) for a portion of the data (e.g.,
explicit lyrics). For instance, data content provider engine 108
may receive at least one alter, remove or replace instruction
(e.g., obscure source information for portions of the video in link
1) from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a remove, alter or replace
data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the remove, alter or replace data instruction to the
data content provider engine 108. The data content provider engine
108 may transmit the anonymize data instruction to the data
modification engine 122 which may then remove, alter or replace the
data. Data modification engine 122 may transmit the data containing
removed, altered or replaced portions to the data content provider
engine 108. Data content provider engine 108 may then display the
data containing removed, altered, or replaced portions. Thus, in
one specific example, a portion of a webpage produced by a search
including data relating to religions other than Catholicism may be
removed from the web page prior to display of the data on a real
machine display such as a computer screen.
[0739] FIG. 101 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2302, and/or an operation 2304.
[0740] The operation 2302 illustrates providing a data display
option of displaying a data portion consistent with at least one
user-related setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one user setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g., OK
to display webpage) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If displayed
data needs to be modified to be consistent with at least one user
setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 (FIG. 1A) may transmit the modified data to the data content
provider engine 108. Data content provider engine 108 may then
display the data consistent with the user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a user setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the user setting. For instance,
a portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[0741] Further, the operation 2304 illustrates providing a data
display option of displaying a data portion consistent with a
privacy related user setting. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination from
data content determination engine 104 (FIG. 1A) post obtaining of
data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one privacy related setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g., OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide an instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a privacy related setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, 13. Effect of content acceptability determination engine
106 may communicate the display instruction to the data content
provider engine 108. If displayed data needs to be modified to be
consistent with at least one privacy related setting, the data
content provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data consistent
with the privacy related setting. For instance, a portion of a
returned webpage including data requesting private user information
such as a user's social security number or e-mail address may be
removed from the web page prior to display of the data on a
computer screen. Further specific examples include a webpage or
website data may be determined to be displayable if the data
satisfies a setting such as a privacy related setting such as a
setting relating to a user's biographical information or financial
information, a webpage or website data may be determined to be
displayable if the data satisfies a group privacy related setting
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting, or a webpage or website data
may be determined to be displayable if the data satisfies a privacy
setting determined by a corporation or other organization to
maintain corporate or organization privacy.
[0742] FIG. 102 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2402.
[0743] The operation 2402 illustrates providing a data display
option of displaying a data portion consistent with a desirability
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g., data
entails an image of format JPEG) from data content determination
engine 104 (FIG. 1A) post obtaining of data by data obtainer engine
102 (FIG. 1A). Effect of content acceptability determination engine
106 may transfer effect of content acceptability determination to
the data provider engine 108 to provide the data display option of
displaying data consistent with at least one desirability setting.
For instance, data content provider engine 108 may receive at least
one display instruction (e.g., OK to display image) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If displayed data needs to be modified
to be consistent with at least one desirability setting, the data
content provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data portion
consistent with the desirability setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with a Christian desirability
setting such as "display only Christianity related data." In other
examples, a webpage or website data may be determined to be
displayable if the data satisfies a desirability setting, a webpage
or website data may be determined to be displayable if the data
satisfies a religious desirability setting such as a Christian,
Jewish, and/or Muslim, based religious desirability setting, or may
be based on any other major, minor or alternative religious
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a political desirability
setting such as a Republican, Democratic, Libertarian or Green
Party political desirability setting, a webpage or website data may
be determined to be displayable if the data satisfies a cultural
desirability setting such as a religious, ethnic, regional, or
heritage based cultural desirability setting or any other cultural
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a theme related
desirability setting such as boating or card games, or a webpage or
website data may be determined to be displayable if the data
satisfies an age appropriateness desirability setting such as a
setting based on the Motion Picture of America Association film
rating system.
[0744] FIG. 103 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2502.
[0745] The operation 2502 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace established setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g., do not display data) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace established setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, 13. Effect of content acceptability determination engine
106 may communicate the display instruction to the data content
provider engine 108. If displayed data needs to be modified to be
consistent with at least one workplace established setting, the
data content provider engine 108 (FIG. 1A) may transmit the modify
data instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data portion
consistent with the workplace established setting. For instance,
the data display option may be displaying on a display of a real
machine only a data portion consistent with a workplace
appropriateness desirability setting such as "display only
non-obscene data."
[0746] FIG. 104 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2602, and/or an operation 2604.
[0747] The operation 2602 illustrates providing a data display
option of displaying a data portion consistent with a safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g., data is an
image) from data content determination engine 104 (FIG. 1A) post
obtaining of data by data obtainer engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one safety setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g., OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate the
display instruction to the data content provider engine 108. If
displayed data needs to be modified to be consistent with at least
one safety setting, the data content provider engine 108 (FIG. 1A)
may transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with child
safety setting such as "display only non-violent data," or "display
only ethnic and gender neutral data."
[0748] Further, the operation 2604 illustrates providing a data
display option of displaying a data portion consistent with a
public safety setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g., data is an
image of format gif) from data content determination engine 104
(FIG. 1A) post obtaining of data by data obtainer engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one desirability setting.
For instance, data content provider engine 108 may receive at least
one display instruction (e.g., OK to display image) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect or content
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If displayed data needs to be modified
to be consistent with at least one public safety setting, the data
content provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data content provider engine 108 may then
display the data portion consistent with the public safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with
public safety setting such as "display only non-confidential
data."
[0749] FIG. 105 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2702.
[0750] The operation 2702 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one child safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a child safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If displayed
data needs to be modified to be consistent with at least one child
safety setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the child safety setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a child safety setting such as "display
only non-violent data."
[0751] FIG. 106 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 2802.
[0752] Further, the operation 2802 illustrates providing a data
display option of displaying a data portion consistent with a home
safety setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one home safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a home safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If displayed
data needs to be modified to be consistent with at least one home
safety setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the home safety setting. For instance, the data display option
may be displaying on a display of a real machine only a data
portion consistent with home safety setting such as "okay to
display private or confidential data."
[0753] FIG. 107 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3502.
[0754] The operation 2902 illustrates providing a data display
option of displaying a data portion consistent with a workplace
safety setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, and/or 13 may include one or more instruction generating
modules configured to provide an instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a workplace safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If displayed data needs to be
modified to be consistent with at least one workplace safety
setting, the data content provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the workplace safety setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a workplace safety setting such as "display
only non-personal data."
[0755] FIG. 108 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3002, an operation 3004, and/or an
operation 3006.
[0756] The operation 3002 illustrates redirecting to alternative
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108, and an
instruction to provide the data display option of redirecting to
alternative data (e.g., another website). For instance, data
content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data.
[0757] Further, the operation 3004 illustrates automatically
redirecting to alternative data. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination from
data content determination engine 104 (FIG. 1A) post obtaining of
data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of redirecting to alternative
data (e.g., another website) consistent with a user preference. For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). At least
one of virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate a
redirect to alternative data consistent with the user preference
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with the user preference. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then automatically (e.g., prior to alerting a user) display the
alternative data. For instance, a real machine 130 may be
automatically redirected to an acceptable web link, or a page of
acceptable data.
[0758] Further, the operation 3006 illustrates providing a list of
selectable alternative data options. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post obtaining
of data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
providing a list of selectable alternative data options (e.g., a
list of alternative websites) consistent with a user preference.
For instance, data content provider engine 108 may receive at least
one provide selectable alternatives instruction from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to transmit a provide selectable alternatives instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the provide
selectable alternatives instruction to the data redirection engine
128 to provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data content provider engine 108.
Data content provider engine 108 may then display the list of
selectable alternatives. For instance, the list of selectable
alternative data options may include a list of acceptable web links
or a selectable list of web pages. Selectable web links and web
pages may include a thumbnail image of the first page of the web
link or of the web page.
[0759] FIG. 109 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3102, and/or an operation 3104.
[0760] The operation 3102 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination (e.g., data does not contain spyware) from data
content determination engine 104 (FIG. 1A) post obtaining of data
by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
displaying data consistent with at least one privacy related
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g., OK to display webpage) from
at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a privacy related setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one privacy related
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data consistent
with the privacy related setting. For instance, a portion of a
returned webpage including data requesting private user information
such as a user's social security number or e-mail address may be
removed from the web page prior to display of the data on a
computer screen. Further specific examples include a webpage or
website data may be determined to be displayable if the data
satisfies a setting such as a privacy related setting such as a
setting relating to a user's biographical information or financial
information, a webpage or website data may be determined to be
displayable if the data satisfies a group privacy related setting
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting, or a webpage or website data
may be determined to be displayable if the data satisfies a privacy
setting determined by a corporation or other organization to
maintain corporate or organization privacy.
[0761] Further, the operation 3104 illustrates displaying
alternative data consistent with a customized user setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data does not contain
malware) from data content determination engine 104 (FIG. 1A) post
obtaining of data by data obtainer engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
displaying data consistent with at least one user setting. For
instance, data content provider engine 108 may receive at least one
display instruction (e.g., OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide an instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one user setting, the data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108. Data content provider engine 108 may then display the
data consistent with the user setting. Thus, a webpage or website
data may be determined to be displayable if the data satisfies a
user setting when at least one of virtual machines 11, 12, and/or
13 compares the data to the user setting. For instance, a portion
of a webpage produced by a search including non-English text may be
removed from the web page prior to display of the data on a
computer screen. Further, in one specific example, a webpage or
website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[0762] FIG. 110 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3202, and/or an operation 3204.
[0763] The operation 3202 illustrates displaying alternative data
consistent with a desirability setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination (e.g., data is an image) from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108, and an
instruction to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g., OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). At least one of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
desirability setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one desirability setting, the data content provider engine
108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the desirability
setting. For instance, the data display option may be displaying on
a display of a real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[0764] Further, the operation 3204 illustrates displaying
alternative data consistent with a workplace established setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g., data is a social
networking site) from data content determination engine 104 (FIG.
1A) post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one workplace
established setting. For instance, data content provider engine 108
may receive at least one display instruction (e.g., do not display
data) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a workplace
established setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one workplace established setting, the data content provider
engine 108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the workplace
established setting. For instance, the data display option may be
displaying on a display of a real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[0765] FIG. 111 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3302.
[0766] The operation 3302 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a user
history setting (e.g., another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user history setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a user history setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a user history setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. For instance, displayed
alternative data may be consistent with a user history such as
having viewed only music related data and pages.
[0767] FIG. 112 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3402, an operation 3404, and/or an
operation 3406.
[0768] The operation 3402 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post obtaining
of data by data obtainer engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine
108, and an instruction to provide the data display option of
redirecting to alternative data consistent with a safety setting
(e.g., another website). For instance, data content provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide a redirect instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a safety setting stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a safety setting instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the redirect data instruction to the data redirection
engine 128 for redirection to alternative data consistent with a
safety setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a safety setting may
include displaying a different webpage including only information
consistent with a safety setting such as "do not display links
requesting credit card information."
[0769] Further, the operation 3404 illustrates displaying
alternative data consistent with a public safety setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination from data content
determination engine 104 (FIG. 1A) post obtaining of data by data
obtainer engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108, and an
instruction to provide the data display option of redirecting to
alternative data consistent with a public safety setting (e.g.,
another website). For instance, data content provider engine 108
may receive at least one redirect instruction from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). At least one of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide a redirect instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a public safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a public safety setting instruction to the data
content provider engine 108. The data content provider engine 108
may transmit the redirect data instruction to the data redirection
engine 128 for redirection to alternative data consistent with a
public safety setting. The data redirection engine 128 may transmit
the redirection to the data content provider engine 108. Data
content provider engine 108 may then display the alternative
data.
[0770] Displaying alternative data consistent with a public safety
setting may include displaying a different webpage including only
information consistent with a public safety setting such as
"display only non-confidential data." Public safety setting may
include a transmittable information safety setting, a viewable
information safety setting and a receivable information safety
setting. Transmittable or viewable information may be private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information.
Receivable information may be any information such as text, images,
a virus, spyware, or any other information that a user's real
machine may be capable of receiving from an external source.
[0771] The operation 3406 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a home
safety setting (e.g., another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a home safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a home safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a home safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a home safety setting may include displaying a
different webpage including only information consistent with a home
safety setting such as "do not display links requesting address
information."
[0772] FIG. 113 illustrates alternative embodiments of the example
operational flow 200C of FIG. 80 where the operation 240 may
include at least one additional operation. Additional operations
may include an operation 3502, and/or an operation 3504.
[0773] The operation 3502 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post obtaining of data by data obtainer engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a
workplace safety setting (e.g., another website). For instance,
data content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the redirect to alternative data consistent with a
workplace safety setting instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a workplace safety
setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a workplace safety
setting may include displaying a different webpage including only
information consistent with a workplace safety setting such as "do
not display links requesting information on this computer."
[0774] Further, the operation 3504 illustrates displaying
alternative data consistent with a child safety setting. Continuing
the example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post obtaining of data by data obtainer engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g., another website). For instance, data content
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a child safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a child safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a child safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data Displaying alternative data
consistent with a child safety setting may include displaying a
different webpage including only information consistent with a
child safety setting such as "do not display links containing
trailers for rated `R` movies."
Application Ser. No. 12/215,692 (1206-003-007A2-000002)
[0775] FIG. 114 illustrates operation 210, which illustrates
retrieving at least a portion of data from a data source (e.g. a
computer accessible from the internet). For example, FIG. 1A
illustrates a data retriever engine 102. Data retriever engine may
retrieve (e.g. download) data 110 (e.g. a web page) from a data
source such as a computer accessible from the internet.
Specifically, data 110 may be web content retrieved from the World
Wide Web via a computing device accessible from the internet. For
example, data retriever engine 102 may set a URL and add a query
string value to the URL. Data retriever engine 102 may then make a
request to the URL and scan the response received from the URL.
Data 110 may be a web site or web page containing one or more links
to additional web sites, such as shown, for example, in FIG. 1B
and/or FIG. 1C. Data 110 may in some instances be textual, a
two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content.
[0776] Then, operation 220 illustrates determining a content of the
data. FIG. 1A illustrates a data content determination engine 104.
Data content determination engine 104 may determine the content
(e.g. text, audio, video, etc.) of the data 110 retrieved from the
data source by the data retriever engine 102. For example, FIG. 1A
illustrates that the data content determination engine 104 may
include a database examination engine 112, a data transverser
engine 114, and a local data examination engine 116. A database
examination engine 112 may examine (e.g. scan) a database (e.g.
information retrieved from a storage server) of known data (e.g.
web links) and compare the known data to the data 110 to determine
data content (e.g. data types such as text, image, audio and/or
video content). Additionally, database examination engine 112 may
compare a portion of data 110 (e.g. a data packet header) against a
database including a collection of data broken down into its
respective components (e.g. header, body). If the comparison yields
a reasonable match, the data type may be determined. Data content
determination may be transmitted from the database examination
engine 112 to the data content determination engine 104.
[0777] A data transverser engine 114 may traverse (e.g. parse) at
least a portion of the data (e.g. a portion of a web page) to
determine data content (e.g. an image or video) within the portion
of the data. Data traversal may occur in real time (e.g.
simultaneously as data is loading). Data content determination may
be transmitted from the data transverser engine 114 to the data
content determination engine 104.
[0778] A local data examination engine 116 may locally (e.g. on the
real machine 130) examine (e.g. analyze) at least a portion of the
data (e.g. data packets) to determine data content (e.g. an audio
file). For instance, local data examination engine 116 may view an
amount of Mill source code to locate markers signifying the type of
data content. Data content determination may be transmitted from
the local data examination engine 116 to the data content
determination engine 104. Data content determination engine 104 may
transmit a data content determination to the Effect of content
acceptability determination engine 106. The content of the data
[0779] 110 may be any textual, audible, or visual content loaded or
displayed after the data is retrieved by the data retriever engine
102. For instance, the content of the data 110 may be a web page
comprising text, sound, and/or an image, a link to a web page, a
video or any combination of text, sound, images, links to web
pages, and videos.
[0780] Then, operation 230 illustrates determining an acceptability
of an effect of the content of the data at least in part via a
virtual machine representation of at least a part of a real machine
having one or more end-user specified preferences. FIG. 1A
illustrates an Effect of content acceptability determination engine
106. Effect of content acceptability determination engine 106 may
receive data and an associated data content determination (e.g.
data is an audio file) from data content determination engine 104
post retrieval of data by data retriever engine 102 and transfer of
retrieved data to data content determination engine 106. Effect of
content acceptability determination engine 106 (FIG. 1A) may
utilize, for example, virtual machine 12 (FIG. 1A) spawned by
virtual machine module 118 to determine whether data associated
with Link 2 would result in a change in the operating system of
real machine 130 contra to user preferences regarding the operating
system as reflected by user preference database 120.
[0781] Then, operation 240 illustrates providing at least one data
display option based on the determining acceptability of the effect
of the content of the data. FIG. 1A illustrates a data provider
engine 108. Data provider engine 108 may be in communication with
Effect of content acceptability determination engine 106, which may
receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
post retrieval of data by data retriever engine 102 and transfer of
retrieved data to data content determination engine 104. Effect of
content acceptability determination engine 106 may transfer at
least effect of content acceptability determination to the data
provider engine 108 to provide at least one data display option. In
one example, data provider engine 108 (FIG. 1A) provides data via
placing the data on a visual display, where the content is such
that it meets one or more thresholds associated with the effect of
content acceptability determination. Provided data may be a list of
web links, a web page, or other data that either have been deemed
acceptable by effect of content acceptability determination engine
106 or that have been modified (e.g., obfuscated), such as by data
modification engine 122, such that the to-be-displayed content is
judged acceptable under user preferences. Provided data may be
modified via the data modification engine 122. For instance,
provided data may be obfuscated via the data obfuscation engine 124
(e.g., at least a portion of the displayed data may be blurred out
or disabled), or provided data may be anonymized via the data
anonymization engine 126 (e.g., at least a portion of the data may
be deleted entirely). Data content provider engine 108 (FIG. 1A)
may receive at least one display instruction (e.g. OK to display
links 1 and 2) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, a each of virtual
machines 11, 12, 13 may include one or more instruction generating
modules configured to provide an instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Such instruction may include an instruction to
the data content provider engine 108 to prevent the data content
provider engine 108 from displaying data that may configure a
hardware profile of real machine 130 counter to anti-viral settings
stored in the user preference database 120 (FIG. 1A), or an
instruction to the data content provider engine 108 to prevent the
data content provider engine 108 from displaying data that may
configure an operating system of real machine 130 counter to a
previous operating system of the real machine (130) (e.g. determine
if a rootkit has been installed).
[0782] FIG. 115 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[0783] Operation 302 illustrates examining a database of known data
for data information. Continuing the example above, data content
determination engine 104 (FIG. 1A) may receive data 110 retrieved
from a data source by the data retriever engine 102 and communicate
data 110 to the database examination engine 112. Database
examination engine 112 may be configured to examine a database of
data provided, for example, by a data provider service or a
database of data stored on a real machine 130. For instance, a
database may include a list of links viewed by a user or
pre-approved by a user based on one or more user-specified
preferences, such as links from a specific source of information
(e.g., the Roman Catholic Church). Database examination engine 112
may communicate the results of a database examination to the data
content determination engine 104.
[0784] Operation 304 illustrates traversing data in real time.
Continuing the example above, database transverser engine 114 (FIG.
1A) examines data received from the data content engine 104
following retrieval of data from the data retriever engine 102.
Data transverser engine 114 may be configured to scan the data 110
to determine a data content type (e.g. an image, a video or an
audio file). Database transverser engine 114 may communicate the
results of a data traversal to the data content determination
engine 104.
[0785] Operation 306 illustrates locally examining data. For
instance, continuing the example above, data content determination
engine 104 (FIG. 1A) may receive data 110 retrieved from a data
source (e.g. a computer accessible through the interne) by the data
retriever engine 102 and communicate data 110 to the local data
examination engine 116. The local examination engine 116 may
examine the data 110 on the real machine 130 at the location of the
real machine 130 (e.g. executed on a subsystem within the real
machine) to determine a data content type (e.g. a downloadable
software program). Local data examination engine 116 may
communicate the results of a local data examination to the data
content determination engine 104.
[0786] FIG. 116 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, an operation 406,
an operation 408, and/or an operation 410.
[0787] Operation 402 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13. Each of virtual
machines 11, 12, and/or 13 may examine (e.g. scan) at least a
portion of data (e.g. an imbedded link on a webpage) to determine
if the data references additional data (e.g. one or more additional
links). Additional data may be a web page comprising text and/or an
image, a link to a web page, a video or any combination of text,
images, links to web pages, or videos. Virtual machines 11, 12, 13
may traverse additional data to determine an acceptability of an
effect of the data content. Effect of content acceptability
determination may be communicated to Effect of content
acceptability determination engine 106 (FIG. 1A) that may
communicate an effect of content acceptability determination to a
data provider engine 108 (FIG. 1A).
[0788] Further, operation 404 illustrates determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine having one or more end-user specified preferences by
determining whether data references additional data when loading.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. Any
of virtual machines
[0789] 11, 12, 13 may examine the data in real time as it loads
onto the virtual machine 11, 12, 13. For instance, if a link to a
webpage immediately (e.g. as soon as the link is activated)
references an additional link (e.g. to redirect a user), a virtual
machine 11, 12, 13 may determine that such a reference to an
additional link has been made. Virtual machines 11, 12; 13 may
determine whether data references additional data at any time when
the data is loading. Effect of content acceptability determination
engine 106 (FIG. 1A) may communicate an effect of content
acceptability determination to a data provider engine 108 (FIG.
1A).
[0790] Operation 406 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13. The data of an
additional link or links may be examined by at least one of virtual
machines 11, 12, 13 issuing a request to receive additional data
information from a remote computer (e.g. a computer at a
geographically distinct location).
[0791] Operation 408 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by examining a copy of
data from a location geographically distinct from a location of the
data. Continuing the example above, FIG. 1A illustrates the Effect
of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102 and
communication of retrieved data to data content determination
engine 104. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12, 13. Effect of
content acceptability determination engine 106 may transfer data
received from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13. The data of an
additional link or links may be examined by at least one of virtual
machines 11, 12, 13 issuing a request to a remote computer to
examine additional data information at the remote computer (e.g. a
computer at a geographically distinct location).
[0792] Further, operation 410 illustrates generating a substantial
duplicate of at least a part of a real machine at a location
geographically distinct from a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. For
instance, a virtual machine 11, 12, 13 of the real machine may be
located at a geographically distinct location such as a remote
server, or a remote system configured duplicate data from the real
machine 130 and to receive and examine real machine information
transferred to the remote server or remote system. System 100 may
include any number of communication modules (not shown) configured
to communicate over local or remote communication channels.
[0793] FIG. 117 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 502, an operation 504, an operation 506,
and/or an operation 508.
[0794] Operation 502 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of a substantial portion of a real machine
having one or more end-user specified preferences. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. For
instance, FIG. 1B illustrates virtual machines 11, 12, 14 including
a virtual machine representation of content of the real machine
130, software or the real machine 130, hardware of the real machine
130, and an operating system of the real machine 130. Virtual
machines 11, 12, 13 may include most or all of at least one of the
content of the real machine 130 (e.g. a substantial portion of the
text, image, audio, and video files of the real machine), software
of the real machine 130 (e.g. a substantial portion of any program
or suite of programs installed on the real machine), hardware of
the real machine 130 (a substantial portion of the circuitry
comprising the real machine), and/or an operating system of the
real machine 130 (e.g. a substantial portion of a Windows.RTM.
operating system installed on the real machine).
[0795] Operation 504 illustrates for determining an acceptability
of an effect of the content of the data at least in part via a
virtual machine representation of at least a portion of data on a
real machine having one or more end-user specified preferences.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 including a virtual
machine representation of content of the real machine 130, a
virtual machine representation of software of the real machine 130,
a virtual machine representation of hardware of the real machine
130, and/or a virtual machine representation of an operating system
of the real machine 130 post activation of link 1, link 2, and link
3 of data 110 (e.g., a Web page) resident on real machine 130.
These post activation states are examples of effects of the content
of data 110. As additional examples, virtual machines 11, 12, 13
may include at least a portion of at least one of the content of
the real machine 130 (e.g. the video files of a real machine),
software or the real machine 130 (e.g. iTunes), hardware of the
real machine 130 (e.g. a data processor), and/or an operating
system of the real machine 130 (e.g. a portion of
Netware.RTM.).
[0796] Operation 506 illustrates determining an acceptability of an
effect of data at least in part via a virtual machine
representation operating at a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B further illustrates virtual machines 11, 12, 13. In one
implementation, any of virtual machines 11, 12, 13 may be generated
on the real machine 130 (e.g. as a subsystem of real machine
130).
[0797] Operation 508 illustrates determining an acceptability of an
effect of data at least in part via a virtual machine
representation operating at a location geographically distinct from
a location of the data. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12, 13. FIG. 1B further illustrates virtual machines
11, 12, 13. In one implementation, any of virtual machines 11, 12,
13 may be generated on a remote server, remote operating system or
otherwise geographically distinct location with respect to the real
machine 130.
[0798] FIG. 118 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 602, an operation 604, an operation 606,
and/or an operation 608.
[0799] Operation 602 illustrates determining an acceptability of an
effect of the content of the data on at least two virtual machine
representations of at least a part of a real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12, 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. FIG. 1B illustrates
virtual machines 11, 12, and 13. At least two of virtual machines
11, 12, 13 may include virtual machine representations of at least
a portion of software, hardware and an operating system of the real
machine 130.
[0800] Further, operation 604 illustrates determining an
acceptability of an effect of the content of the data on at least
two virtual machine representations of at least a part of a real
machine having one or more end-user specified preferences at least
one of the at least two virtual machine representations operating
on a separate operating system. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12, 13. For instance, a virtual machine 11, 12, 13
(FIG. 1A) may individually mimic one of Windows XP, Windows 2000
with SQL 2000 and SharePoint Server 2003, Windows 2003 with
Exchange 2003, an Apple operating system (e.g., MAC OS 9, OS X
Leopard), or Red Hat Linux with Apache. Further, each virtual
machine 11, 12, 13 may mimic a different operating system (e.g.,
virtual machine 11 may mimic Windows XP, virtual machine 12 may
mimic Windows 2000 and virtual machine 13 may mimic Red Hat Linux
and so on). Operating system may be any software configured to
manage the sharing of the resources of a computer, process system
data and user inputs, and respond to user inputs by allocating and
managing tasks and internal system resources. Operating system may
be, for example Microsoft Windows.RTM. 2000, XP, or Vista available
from Microsoft Corporation of Redmond, Wash., Mac OS X, Linux or
any other operating system.
[0801] Operation 606 illustrates determining an acceptability of an
effect of the content of the data on at least two virtual machine
representations of at least a part of a real machine having one or
more end-user specified preferences, at least one of the at least
two virtual machine representations operating on a separate core of
a system comprising at least two cores. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12, 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. As illustrated in FIGS.
1B and 1C, each of virtual machine 11, virtual machine 12, virtual
machine 13, virtual machine 21, virtual machine 22, and virtual
machine 23 may operate on an individual core 11, 12, 13, 31, 32,
33, respectively, of a multi-core processor, or virtual machine 11
may run on one core and virtual machines 12, 13 may run on the
other core of a dual core processor such as an Intel.RTM. dual core
processor and so on. The multi-core processor may include a
plurality of processor cores packaged in one processor package. The
term core as used herein may refer, for example, to a single
processor of a multiprocessor system, or to a processor core of a
multi-core processor. Multi-core processor may be utilized as
portable computers such as laptop computers, personal digital
assistants, or desktop computers, or servers, or another form of
processor based system. Combinations of these types of platforms
may be present. The multi-core system may include a multi-core
processor, each core comprising a separate address space, and
having internal to that address space.
[0802] Operation 608, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location of the data. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12, 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. Each of virtual machines
11, 12, 13 may operate on a separate operating system at a location
of the data (e.g. executed on a subsystem, such as the virtual
machine module 118 (FIG. A) including a plurality of virtual
machines 11, 12, 13 (FIG. 1B) within the real machine 130).
[0803] FIG. 119 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 702, an operation 704, an operation 706,
and/or an operation 708.
[0804] Operation 702 illustrates determining a state change of a
virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer the data
and associated data content determination to at least one of
virtual machines 11, 12, 13. A state change (e.g. a decrease in
memory) of virtual machine 11, 12, 13 (FIG. 1B) may be determined
by a component of virtual machine 11, 12, 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[0805] Operation 704 illustrates determining a state of a virtual
machine representation prior to loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12, 13.
Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. Virtual machine 11, 12,
13 may determine a state of at least one component (e.g. the
hardware) of the virtual machine prior to activation (e.g. before)
of a link. Virtual machine state may be representative of a state
for all or at least a portion of the components (e.g. content,
software, hardware, operating system) of the real machine 130
represented by the virtual machine 11, 12, and 13. For instance, a
virtual machine 11, 12, 13 may be determined to be free of viruses,
an amount of virtual machine memory may be measured, or a
processing speed of the virtual machine 11, 12, 13 may be
determined. Virtual machines 11, 12, 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[0806] Further, operation 706 illustrates determining a state of a
virtual machine after loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12, 13.
Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12, 13. Virtual machine 11, 12,
13 may determine a state of at least one component (e.g. the
hardware) of the virtual machine subsequent to (e.g. after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by the virtual machine 11, 12, 13 after at least a
portion of the data has loaded. For instance, a virtual machine 11,
12, 13 may be determined to contain a virus, an amount of virtual
machine memory may be measured, or a processing speed of the
virtual machine 11, 12, 13 may be determined. Virtual machine 11,
12, 13 may be examined to determine, for example, if a virus or any
other undesired software is present on the machine after at least a
portion of the data has loaded by examining the virtual machine
representation of the operating system of the real machine 130
(FIG. 1B), or if information from the real machine 130 has been
transferred to an external location by examining the software of
the real machine 130.
[0807] Operation 708 illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data and associated data
content determination to at least one of virtual machines 11, 12,
13. An undesirable state change may be determined by examining the
changes to the virtual machine 11, 12, 13 and comparing the state
change of the virtual machine 11, 12, 13 to user preference
database information spawned on virtual machines 11, 12, 13 by a
transfer of user preference database information from the user
preference database 120 (FIG. 1A) to the virtual machine module 118
(FIG. 1A) which spawns a copy of at least a portion of the user
preference database 120 (FIG. 1A) onto virtual machines 11, 12, 13.
A state change may include any undesirable state changes such as a
decrease in memory or processing speed and/or the presence of a
virus or other undesirable software after at least a portion of the
data has loaded. Undesirable state changes may further include an
undesirable transfer of information located on the virtual machine
11, 12, 13 to an external location, an undesirable transfer of data
onto the virtual machine 11, 12, 13 from an external location after
at least a portion of the data has loaded on the virtual machine
11, 12, 13 that may result in an undesired change in the state of
content, software, hardware or an operating system of the real
machine 130 and/or an undesirable transfer of data onto the virtual
machine 11, 12, 13 where at least a portion of the transferred data
may be found objectionable when viewed by a user 10.
[0808] FIG. 120 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 802, an operation 804, an operation 806, an
operation 808, and/or an operation 810.
[0809] Operation 802 illustrates determining an acceptability of an
effect of the content of the data in response to at least one user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post retrieval of data by
data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, 13. An
undesirable state change may be determined by examining the changes
to the virtual machine 11, 12, 13 and comparing the state change of
the virtual machine 11, 12, 13 to user preference database
information spawned on virtual machines 11, 12, 13 by a transfer of
user preference database information from the user preference
database 120 (FIG. 1A) to the virtual machine module 118 (FIG. 1A)
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12, 13. User
preference database 120 may include at least one end-user specified
preference relating to at least one of content, software, hardware
and/or an operating system of a real machine 130. At least one of
virtual machines 11, 12, 13 may determine an acceptability of an
effect of the content of the data based on at least one user
setting contained in a user preference database at least a portion
of which may be spawned onto virtual machines 11, 12, 13 via
virtual machine module 118 (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a setting established by a user such as a political or
cultural preference setting). Further examples of user preferences
include specific religion or lifestyle preference, such as "return
only links relating to Roman Catholicism" or "return only links
relating to a vegan lifestyle" that may be stored in the real
machine 130. User-specific preference may also relate to user
information safety or computer safety, such as "do not display
links requesting information from my computer," or "do not display
links that transfer viruses onto my computer."
[0810] Operation 804 illustrates determining an acceptability of an
effect of the content of the data in response to a personal user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post retrieval of data by
data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, 13. User
preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12, 13. Virtual machines 11, 12, 13 may compare the data
received from the virtual machine module to a personal user setting
(e.g. "show only automobile related data") contained in user
preference database information spawned on virtual machines 11, 12,
13. User preference database 120 may include at least one personal
user setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130. Personal
user setting may be a setting input by a user that is personal to
the user, such as an information security level, a content filter
level, or a personal desirability setting such as "show only
non-religious data" or "show only automobile related data."
[0811] Further, operation 806 illustrates determining an
acceptability of an effect of the content of the data in response
to a peer user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module to a peer user
setting contained in user preference database information spawned
on virtual machines 11, 12, 13. User preference database 120 may
include at least one peer user setting relating to at least one of
content, software, hardware and/or an operating system of a real
machine 130. Peer user setting may be a setting input by a user
that is determined by a peer group, such as a peer group determined
information security level such as "display only 100 percent secure
websites", a peer group determined data filter level such as
"filter 100% of obscene data", or a peer group desirability setting
such as "show only classical music related data" or "show only
knitting related data."
[0812] Additionally, operation 808 illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a corporate
user setting contained in user preference database information
spawned on virtual machines 11, 12, 13. User preference database
120 may include at least one corporate user setting relating to at
least one of content, software, hardware and/or an operating system
of a real machine 130. Corporate user setting may be a setting
input by a corporation that is determined to the corporation, such
as a corporate desirability setting such as "show only real-estate
related data" or "show only agricultural related data."
[0813] Further, operation 810 illustrates determining an
acceptability of an effect of the content of the data in response
to a work safety user setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a work safety
user setting contained in user preference database information
spawned on virtual machines 11, 12, 13. User preference database
120 may include at least one work safety user setting relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. Thus, in one specific example, a
webpage or website data may be determined to be determined to be
displayable if the data satisfies a work safety user setting such
as a corporate information security level, corporate user setting,
or a corporate information content filter level corporate user
setting.
[0814] FIG. 121 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 902, an operation 904, an operation 906, an
operation 908, an operation 910, and/or an operation 912.
[0815] Operation 902 illustrates determining an acceptability of an
effect of the content of the data in response to a desirability
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12, 13. Upon receiving data and a data content determination from
data content determination engine 104 post retrieval of data by
data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12, 13. User
preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12, 13. Virtual machines 11, 12, 13 may compare the data
received from the virtual machine module 118 to a desirability
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a desirability
setting established by a user such as a desire to view only
non-obscene material) contained in user preference database
information spawned on virtual machines 11, 12, 13. User preference
database 120 may include at least one desirability setting relating
to at least one of content, software, hardware and/or an operating
system of a real machine 130.
[0816] Operation 904 illustrates determining an acceptability of an
effect of the content of the data in response to a religious
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a religious
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a religious desirability setting established by a user such as a
desire to view only Hindu material) contained in user preference
database information spawned on virtual machines 11, 12, 13. A
religious desirability setting may be include any setting regarding
a major, minor, or other religion such as Christianity, Judaism,
Islam, Hinduism, and so on.
[0817] Operation 906 illustrates determining an acceptability of an
effect of the content of the data in response to a political
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a political
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a political desirability setting established by a user such as a
desire to view only Democratic Party material) contained in user
preference database information spawned on virtual machines 11, 12,
13. A political desirability setting may include any setting
regarding a political party or affiliation (e.g. Republican,
Democratic, Libertarian, Green Party, etc.).
[0818] Operation 908 illustrates determining an acceptability of an
effect of the content of the data in response to a cultural
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a cultural
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
a cultural desirability setting established by a user such as a
desire to view only materials regarding early Mayan civilization)
contained in user preference database information spawned on
virtual machines 11, 12, 13. A cultural desirability setting may
include any culturally related information such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting.
[0819] Operation 910 illustrates determining an acceptability of an
effect of the content of the data in response to a theme related
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a theme
related desirability setting (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a theme related desirability setting established by a user
such as a desire to view only materials regarding collectible
stamps) contained in user preference database information spawned
on virtual machines 11, 12, 13. A theme related desirability
setting may include any theme related information, such as
information relating to cars, fashion, electronics, sports,
hobbies, collector's items, or any theme or category that may be of
interest to a user.
[0820] Operation 912 illustrates determining an acceptability of an
effect of the content of the data in response to an age
appropriateness desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to an
age appropriateness desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on an age appropriateness desirability
setting established by a user such as a desire to view only
materials given a PG or lower rating as determined by the Motion
Picture of America Association film rating system) contained in
user preference database information spawned on virtual machines
11, 12, 13. An age appropriateness desirability setting may include
any age appropriate setting, such as a rating threshold or a
profanity threshold.
[0821] FIG. 122 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 1002, an operation 1004, an operation 1006,
and/or an operation 1008.
[0822] Operation 1002 illustrates determining an acceptability of
an effect of the content of the data in response to at least one
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a privacy
related setting (e.g., does a website contain only images, text,
audio or visual data suitable for viewing by a user based on a
privacy related setting established by a user) contained in user
preference database information spawned on virtual machines 11, 12,
13. A privacy related setting may include any privacy related
settings (e.g., does a website contain only data that will not
request information from my computer or allow others to view
personal information saved on my computer).
[0823] Operation 1004 illustrates determining an acceptability of
an effect of the content of the data in response to a user specific
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to a user
specific privacy related setting (e.g., will a website request
specific information about the user such as name, address,
telephone number) contained in user preference database information
spawned on virtual machines 11, 12, 13. A user specific privacy
related setting may include any user specific privacy related
settings (e.g., a setting relating to a user's biographical
information or financial information).
[0824] Further, operation 1006 illustrates determining an
acceptability of an effect of the content of the data in response
to a group privacy related setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to a
group privacy related setting (e.g., will a website request
information about an organization such as name, address, telephone
number) contained in user preference database information spawned
on virtual machines 11, 12, 13. A group privacy related setting may
include any group privacy related settings (e.g., a setting
relating to a group's membership). Group privacy related setting
may be any setting established by a group such as a work group
(e.g. employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g. members of family unit) privacy
related setting.
[0825] Further, operation 1008 illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate privacy related setting. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to a
corporate privacy related setting (e.g., will a website request
information about a corporation such as data stored on a real
machine belonging to the corporation) contained in user preference
database information spawned on virtual machines 11, 12, 13.
Corporate privacy related setting may be determined by a corporate
issued privacy manual, or other such document or mandate set forth
by officers of a corporation.
[0826] FIG. 123 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 1102, an operation 1104, an operation 1106,
and/or an operation 1108.
[0827] Operation 1102 illustrates determining an acceptability of
an effect of the content of the data in response to a type of
transmitted user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. Virtual machines 11, 12, 13 may compare the
data received from the virtual machine module 118 to at least one
acceptable type of transmitted user information setting (e.g., do
not return links that will transmit my e-mail address, home address
or telephone number to an external location) contained in user
preference database information spawned on virtual machines 11, 12,
13. Acceptable type of transmitted user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be transmitted to a location external to the
real machine by selecting the link.
[0828] Further, operation 1104 illustrates determining an
acceptability of an effect of the content of the data in response
to a type of captured user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to at
least one acceptable type of captured user information setting
(e.g., do not return links that will capture my e-mail address,
home address or telephone number) contained in user preference
database information spawned on virtual machines 11, 12, 13.
Acceptable type of captured user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be captured by a machine located at a location
external to the real machine by selecting the link.
[0829] Further, operation 1106 illustrates determining an
acceptability of an effect of the content of the data in response
to a type of exposed user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12, 13. Upon receiving data
and a data content determination from data content determination
engine 104 post retrieval of data by data retriever engine 102,
Effect of content acceptability determination engine 106 may
transfer the data and associated data content determination to
virtual machine module 118. Virtual machine module 118 may spawn at
least one virtual machine 11, 12, and/or 13 and transfer data and
associated data content determination to at least one of virtual
machines 11, 12, 13. User preference database information stored in
the user preference database 120 (FIG. 1A) may be transferred to
the virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12, 13. Virtual machines 11, 12, 13 may
compare the data received from the virtual machine module 118 to at
least one acceptable type of exposed user information setting
(e.g., do not return links that will expose personal financial
information stored on the real machine 130) contained in user
preference database information spawned on virtual machines 11, 12,
13. Acceptable type of exposed user information setting may be
determined by a user 10 (FIG. 1B). For instance, acceptability of
the effect of the data may be determined in response to whether or
not private user information, such as credit card numbers, bank
accounts, personal identification information or any other personal
user information may be exposed to a machine located at a location
external to the real machine by selecting the link.
[0830] Operation 1108 illustrates determining an acceptability of
an effect of the content of the data in response to visually
examining a data image. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. To visually examine a data image, a virtual machine 11, 12, 13
may include an image scanning module. Visually examining the data
image may include, for example, color analysis, pattern-matching,
pattern-recognition, or any other technique for recognizing a
particular image or type of image.
[0831] FIG. 124 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the determining an
acceptability of the effect of the data of the data operation 230
may include at least one additional operation. Additional
operations may include an operation 1202.
[0832] Operation 1202, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location geographically distinct from a
location of the data. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12, 13. Upon receiving data and a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102, Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to virtual machine module
118. Virtual machine module 118 may spawn at least one virtual
machine 11, 12, and/or 13 and transfer data and associated data
content determination to at least one of virtual machines 11, 12,
13. User preference database information stored in the user
preference database 120 (FIG. 1A) may be transferred to the virtual
machine module 118 (FIG. 1A), which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12, 13. At least two virtual machines, for example
virtual machines 12, 13 may be virtual machines operating at
geographically distinct location such as a remote server, or a
remote system configured to receive and examine real machine
information transferred to the remote system and duplicate data
from the real machine 130. In some instances, each virtual machine
may be generated on one or more separate cores of a multi-core
processor.
[0833] FIG. 125 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1302, an operation 1304, an operation 1306, an operation
1308, and/or an operation 1310.
[0834] Operation 1302 illustrates providing a data display option
of displaying the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
video file) from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display the entire text of link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. Data content provider engine 108 may
then display the data. Displayed data may be an unmodified web page
of text, images and/or video, or a web page including links to
additional web pages and may be displayed on a real machine display
such as a computer screen.
[0835] Operation 1304 illustrates providing a data display option
of not displaying the data. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of not
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one do not display
instruction (e.g. Do not display the text of link 1) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12, 13 may
include one or more instruction generating modules configured to
provide a do not display instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the do not display instruction to the
data content provider engine 108. The data display option of not
displaying the data may include a message indicated why the data is
not being displayed, or may be, for example, a blank page displayed
on a display of the real machine.
[0836] Operation 1306 illustrates providing a data display option
of displaying a modified version of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a portion of
the data. For instance, data content provider engine 108 may
receive at least one modify data instruction (e.g. display only
lines 1-10 of the text of link 1) from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to provide a modify data
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, 13. Effect of
content acceptability determination engine 106 may communicate the
modify data instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine may transmit the modified data
to the data content provider engine 108. Data content provider
engine 108 may then display the modified version of the data.
Displayed data may be an modified web page of text, a modified
images and/or a modified video, or a modified web page including
links to additional web pages. For instance, a webpage or website
may be displaying, but any obscenities on the web page or website
may replaced by non-obscene word alternatives.
[0837] Further, operation 1308 illustrates providing a data display
option of obfuscating an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of obfuscating (e.g. blurring) a
portion of the data (e.g. obscene photos). For instance, data
content provider engine 108 may receive at least one obfuscate data
instruction (e.g. display only non-obscene portions of the image in
link 1) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12, 13 may include one or more instruction generating
modules configured to provide an obfuscate data instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the obfuscate data
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the obfuscate data
instruction to the data modification engine 122 which may transmit
the obfuscate data instruction to the data obfuscation engine 124.
Data obfuscation engine 124 may transmit the obfuscated data to the
data modification engine 122 for transmission to the data content
provider engine 108. Data content provider engine 108 may then
display the obfuscated version of the data. For example,
obfuscating logic may obfuscate restricted data or imagery within a
webpage or image. Obfuscation may include blurring or blocking of
the objectionable data portion.
[0838] Further, operation 1310 illustrates providing a data display
option of anonymizing an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of anonymizing (e.g. obscuring
source information) for a portion of the data (e.g. graphic
videos). For instance, data content provider engine 108 may receive
at least one anonymize data instruction (e.g. obscure source
information for portions of the video in link 1) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12, 13 may include one
or more instruction generating modules configured to provide an
anonymize data instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12, 13.
Effect of content acceptability determination engine 106 may
communicate the anonymize data instruction to the data content
provider engine 108. The data content provider engine 108 may
transmit the anonymize data instruction to the data modification
engine 122 which may transmit the anonymize data instruction to the
data anonymization engine 126. Data anonymization engine 126 may
transmit the anonymized data to the data modification engine 122
for transmission to the data content provider engine 108. Data
content provider engine 108 may then display the anonymized version
of the data. Anonymized data may be data in which the original
identity information of the data is hidden, obscured, replaced,
and/or otherwise modified.
[0839] FIG. 126 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1402, an operation 1404, an operation 1406, and/or an
operation 1408.
[0840] Operation 1402 illustrates providing a data display option
of removing, altering, or replacing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an audio file)
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of removing, altering or
replacing an objectionable data portion (e.g. replacing profanity
with innocuous language) for a portion of the data (e.g. explicit
lyrics). For instance, data content provider engine 108 may receive
at least one alter, remove or replace instruction (e.g. obscure
source information for portions of the video in link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the remove,
alter or replace data instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
anonymize data instruction to the data modification engine 122
which may then remove, alter or replace the data. Data modification
engine 122 may transmit the data containing removed, altered or
replaced portions to the data content provider engine 108. Data
content provider engine 108 may then display the data containing
removed, altered, or replaced portions. Thus, in one specific
example, a portion of a webpage produced by a search including data
relating to religions other than Catholicism may be removed from
the web page prior to display of the data on a real machine display
such as a computer screen.
[0841] Operation 1404 illustrates providing a data display option
of displaying a data portion consistent with at least one setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is text) from data
content determination engine 104 (FIG. 1A) post retrieval of data
by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g. OK to
display only text consistent with a corporate established setting)
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, 13. Effect of content acceptability determination engine
106 may communicate the display instruction to the data content
provider engine 108. If data needs to be modified to be consistent
with at least one setting, the data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108 (e.g., a setting such as recast all text to large, and
reformat a page consistent with the large text, such as might be
done for an individual having special vision needs). Data content
provider engine 108 may then display the data consistent with the
setting.
[0842] Further, operation 1406 illustrates providing a data display
option of displaying a data portion consistent with a privacy
related setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data does
not contain spyware) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one privacy related
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g. OK to display webpage) from
at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a privacy related setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one privacy related setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data consistent with the privacy
related setting. For instance, a portion of a returned webpage
including data requesting private user information such as a user's
social security number or e-mail address may be removed from the
web page prior to display of the data on a computer screen. Further
specific examples include a webpage or website data may be
determined to be displayable if the data satisfies a setting such
as a privacy related setting such as a setting relating to a user's
biographical information or financial information, a webpage or
website data may be determined to be displayable if the data
satisfies a group privacy related setting such as a work group
(e.g. employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g. members of family unit) privacy
related setting, or a webpage or website data may be determined to
be displayable if the data satisfies a privacy setting determined
by a corporation or other organization to maintain corporate or
organization privacy.
[0843] Further, operation 1408 illustrates providing a data display
option of displaying a data portion consistent with a user setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data does not contain
malware) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one user setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12, 13 may include one
or more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one user setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data consistent with the user
setting. Thus, a webpage or website data may be determined to be
displayable if the data satisfies a user setting when the virtual
machine 11, 12, 13 compares the data to the user setting. For
instance, a portion of a webpage produced by a search including
non-English text may be removed from the web page prior to display
of the data on a computer screen. Further, in one specific example,
a webpage or website data may be determined to be displayable if
the data satisfies a peer user setting, or a webpage or website
data may be determined to be displayable if the data satisfies, for
instance, a corporate user setting.
[0844] FIG. 127 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1502, and/or an operation 1504.
[0845] Operation 1502 illustrates providing a data display option
of displaying a data portion consistent with a desirability
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a desirability
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one desirability
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data modification engine 122 may transmit
the modified data to the data content provider engine 108. Data
content provider engine 108 may then display the data portion
consistent with the desirability setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with a Christian desirability
setting such as "display only Christianity related data." In other
examples, a webpage or website data may be determined to be
displayable if the data satisfies a desirability setting, a webpage
or website data may be determined to be displayable if the data
satisfies a religious desirability setting such as a Christian,
Jewish, and/or Muslim, based religious desirability setting, or may
be based on any other major, minor or alternative religious
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a political desirability
setting such as a Republican, Democratic, Libertarian or Green
Party political desirability setting, a webpage or website data may
be determined to be displayable if the data satisfies a cultural
desirability setting such as a religious, ethnic, regional, or
heritage based cultural desirability setting or any other cultural
desirability setting, a webpage or website data may be determined
to be displayable if the data satisfies a theme related
desirability setting such as boating or card games, or a webpage or
website data may be determined to be displayable if the data
satisfies an age appropriateness desirability setting such as a
setting based on the Motion Picture of America Association film
rating system.
[0846] Further, operation 1504 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
social networking site) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one workplace established
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g. do not display data) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace established setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace established setting,
the data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data portion consistent with the
workplace established setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a workplace appropriateness desirability
setting such as "display only non-obscene data."
[0847] FIG. 128 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1602, an operation 1604, and/or an operation 1606.
[0848] Operation 1602 illustrates providing a data display option
of displaying a data portion consistent with a safety setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an image) from
data content determination engine 104 (FIG. 1A) post retrieval of
data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
(e.g. OK to display image) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one safety setting, the data content
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with child
safety setting such as "display only non-violent data," or "display
only ethnic and gender neutral data."
[0849] Further, operation 1604 illustrates providing a data display
option of displaying a data portion consistent with a public safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a desirability
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one public safety
setting, the data content provider engine 108 may transmit the
modify data instruction to the data modification engine 122 for
modification of the data. Data content provider engine 108 may then
display the data portion consistent with the public safety setting.
For instance, the data display option may be displaying on a
display of a real machine only a data portion consistent with
public safety setting such as "display only non-confidential
data."
[0850] Further, operation 1606 illustrates providing a data display
option of displaying a data portion consistent with a home safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one home safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a home safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If data needs to be modified to be
consistent with at least one home safety setting, the data content
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
content provider engine 108 may then display the data portion
consistent with the home safety setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with home safety setting such as
"okay to display private or confidential data."
[0851] FIG. 129 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1702, and/or an operation 1704.
[0852] Operation 1702 illustrates providing a data display option
of displaying a data portion consistent with a workplace safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace safety setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace safety setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a workplace
safety setting such as "display only non-personal data."
[0853] Further, operation 1704 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one child safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a child safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If data needs to be modified to be
consistent with at least one child safety setting, the data content
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
content provider engine 108 may then display the data portion
consistent with the child safety setting. For instance, the data
display option may be displaying on a display of a real machine
only a data portion consistent with a child safety setting such as
"display only non-violent data."
[0854] FIG. 130 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1802, an operation 1804, an operation 1806, and/or an
operation 1808.
[0855] Operation 1802 illustrates redirecting to alternative data a
user may be redirected to alternative data. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data.
[0856] Operation 1804 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a privacy related
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a privacy related setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a privacy related setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a privacy related setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a privacy related setting may include displaying a
different webpage including only information consistent with a
privacy related setting such as "display only links that do not
request e-mail addresses." Privacy related setting may be any
privacy related setting described above and may include any
additional privacy related settings.
[0857] Further, operation 1806 illustrates displaying alternative
data consistent with a customized user setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a customized user
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a customized user setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a customized user setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a customized user setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a customized user setting may include displaying a
different webpage including only information consistent with a
customized user setting such as "display only links containing
French text." Thus, in one specific example, a webpage or website
data may be determined to be displayable if the data satisfies a
customized user setting when the virtual machine 11, 12, 13
compares the data to the customized user setting.
[0858] Further, operation 1808 illustrates displaying alternative
data consistent with a desirability setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a desirability
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a desirability setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a desirability setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a desirability setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
desirability setting may include displaying a different webpage
including only information consistent with a desirability setting
such as "display only links containing information relating to
art." Desirability setting may be any desirability setting
described above and may include any additional desirability
settings.
[0859] FIG. 131 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1902, and/or an operation 1904.
[0860] Operation 1902 illustrates displaying alternative data
consistent with a workplace established setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace
established setting (e.g. another website). For instance, data
content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12, 13 may include one or more instruction generating
modules configured to provide a redirect instruction to the Effect
of content acceptability determination engine 106 after a
comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, 13. Effect of content
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a workplace established setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace established setting.
The data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a workplace established setting may include
displaying a different webpage including only information
consistent with a workplace established setting such as "do not
display links to social networking websites."
[0861] Operation 1904 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a user history
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user history setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a user history setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. For instance, displayed alternative data may be
consistent with a user history such as having viewed only music
related data and pages.
[0862] FIG. 132 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 2002, an operation 2004, and/or an operation 2006.
[0863] Operation 2002 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of redirecting to alternative
data consistent with a safety setting (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a safety setting stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a safety setting instruction to
the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a safety setting. The data redirection engine 128
may transmit the redirection to the data content provider engine
108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
safety setting may include displaying a different webpage including
only information consistent with a safety setting such as "do not
display links requesting credit card information."
[0864] Operation 2004 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a workplace safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a workplace safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace safety setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a workplace safety setting may include displaying a
different webpage including only information consistent with a
workplace safety setting such as "do not display links requesting
information on this computer."
[0865] Operation 2006 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a child safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a child safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a child safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
child safety setting may include displaying a different webpage
including only information consistent with a child safety setting
such as "do not display links containing trailers for rated `R`
movies."
[0866] FIG. 133 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 2102, an operation 2104, an operation 2106, and/or an
operation 2108.
[0867] Operation 2102 illustrates displaying alternative data
consistent with a public safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a public safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a public safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a public safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a public safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a public safety setting may include displaying a
different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[0868] Operation 2104 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a home safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11,
12, 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a home safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a home safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
home safety setting may include displaying a different webpage
including only information consistent with a home safety setting
such as "do not display links requesting address information."
[0869] Operation 2106 illustrates automatically redirecting to
alternative data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of redirecting to alternative data
(e.g. another website) consistent with a user preference. For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12, 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with the user preference instruction to
the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with the user preference. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then automatically
(e.g. prior to alerting a user) display the alternative data. For
instance, a real machine 130 may be automatically redirected to an
acceptable web link, or a page of acceptable data.
[0870] Further, operation 2108 illustrates providing a list of
selectable alternative data options. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of providing a list of
selectable alternative data options (e.g. a list of alternative
websites) consistent with a user preference. For instance, data
content provider engine 108 may receive at least one provide
selectable alternatives instruction from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12, 13 may include one or more
instruction generating modules configured to transmit a provide
selectable alternatives instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, 13. Effect of content acceptability determination
engine 106 may communicate the provide selectable alternatives
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the provide selectable
alternatives instruction to the data redirection engine 128 to
provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data content provider engine 108.
Data content provider engine 108 may then display the list of
selectable alternatives. For instance, the list of selectable
alternative data options may include a list of acceptable web links
or a selectable list of web pages. Selectable web links and web
pages may include a thumbnail image of the first page of the web
link or of the web page.
[0871] FIG. 134 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 230 may include at least one
additional operation. Additional operations may include an
operation 2202, an operation 2204, an operation 2206, and/or an
operation 2208.
[0872] At the operation 2202, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2, and/or link 3 actually been traversed on real machine 130). FIG.
1B further illustrates virtual machines 11, 12, 13 including a
virtual machine representation of content of the real machine 130
post activation of Link 1, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
email, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation may include determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine include determining whether or not a video or image
has been loaded onto, for example, the virtual machine 11 after
loading at least a portion of the data contained in Link 1.
[0873] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine on a
virtual machine representation of at least a portion of a real
machine generated by, for example, virtual machine 11. FIG. 1C
illustrates a partial follow-on operational view of real machine
130 (e.g., a desktop, notebook, or other type computing system) in
which at least a portion of system 100 (FIG. 1A) has been
implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0874] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6 post traversal of
Link 1. Accordingly, FIG. 1C illustrates system 100 generating
virtual machine representations of real machine 130, used to
traverse Links 4, 5, and 6, in the context of virtual machines 21,
22, and 23, respectively. Those skilled in the art will thus
appreciate that, in the example shown in FIG. 1C, system 100 is
creating second-order virtual machine representations to
prospectively investigate the effects on the states of various
components of real machine 130 via sequential traversals of links.
That is, the virtual machine representations of real machine 130
encompassed in virtual machine 21, virtual machine 22, and virtual
machine 23 of FIG. 1C are generated by system 100 based on the
first-order virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0875] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of content
(e.g., a movie, web page, music file, etc.) of the real machine 130
post sequential activation of Link 1 then Link 4, virtual machine
22 including a virtual machine representation of content (e.g. a
graphical image, a text file, an email, etc) of the real machine
130 post (e.g., subsequent to) sequential activation of Link 1 then
Link 5, and virtual machine 23 encompassing a virtual machine
representation of the content (e.g. a music file) of the real
machine 130 post sequential activation of Link 1 then Link 6. A
determination of an acceptability of an effect of the content of
data on the content of the real machine made on virtual machine 21
may include determining whether or not an audio file has been
loaded onto virtual machine 21. Virtual machine 21 may communicate
a determination of an acceptability of an effect of the content of
data determination made on a virtual machine 21 which may be at
least a portion of content of the real machine to virtual machine
11, which may communicate the acceptability of an effect of the
content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0876] At the operation 2204, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2, and/or link 3 actually been traversed on real machine 130). FIG.
1B illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software) of the real
machine 130 post (e.g. subsequent to) activation of Link 1.
Examples of such software might include a commercial word
processing program or suite of programs (e.g. Microsoft.RTM. Office
for Windows), an open source Web browser (e.g., Mozilla's
Firefox.RTM. Browser), an AJAX mash up (e.g., an executing
JavaScript.TM. and/or data retrieved by same via an XML-like
scheme), or a commercial database management system (e.g., one or
more of Oracle Corporation's various products), a commercial
anti-malware/spyware programs (e.g., such as those of Symantec
Corporation or McAfee, Inc.), etc. An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation may include determining
an acceptability of an effect of the content of the data at least
in part via a virtual machine representation of at least a portion
of the software of the real machine include determining whether or
not an unauthorized program or suite of programs (e.g. music
downloading software) has been loaded, for example, onto virtual
machine 12 after loading at least a portion of the data contained
in Link 2.
[0877] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine on a
virtual machine representation of at least a portion of the
software of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0878] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0879] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
software (e.g.) of the real machine 130 post sequential activation
of Link 1 then Link 4, virtual machine 22 including a virtual
machine representation of software (e.g. an AJAX mashup) of the
real machine 130 post sequential activation of Link 1 then Link 5,
and a virtual machine representation of the software (e.g. a
commercial database management system) of the real machine 130 post
sequential activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the software
of the real machine made on virtual machine 21 may include
determining whether or not malware or grayware has been loaded onto
virtual machine 21. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
software of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0880] At the operation 2206, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the hardware of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12, 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2 or link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of hardware (e.g. a state of the hardware) of the
real machine 130 post activation of Link 1. Examples of such
hardware might include all or part of a chipset (e.g., data
processor and/or graphics processor chipsets such as those of Intel
Corporation and/or NvidiaCorporation), a memory chip (e.g., flash
memory and/or random access memories such as those of Sandisk
Corporation and/or Samsung Electronics, Co., LTD), a data bus, a
hard disk (e.g., such as those of Seagate Technology, LLC), a
network adapter (e.g., wireless and/or wired LAN adapters such as
those of Linksys and/or CiscoTechnology, Inc.), printer, a
removable drive (e.g., flash drive), a cell phone, etc. An example
of determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a portion of the hardware of the real machine include
determining whether a network adapter on, for example, virtual
machine 12 has been disabled after loading at least a portion of
the data contained in Link 2.
[0881] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine on a
virtual machine representation of at least a portion of the
hardware of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0882] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0883] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
hardware (e.g. the circuitry or processor of the real machine) of
the real machine 130 post sequential activation of Link 1 then Link
4, a virtual machine representation of hardware (e.g. a network
adapter) of the real machine 130 post sequential activation of Link
1 then Link 5, and a virtual machine representation of the hardware
(e.g. a removable drive) of the real machine 130 post sequential
activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the hardware
of the real machine made on virtual machine 21 may include
determining whether a decrease in processor speed of virtual
machine 21 has occurred. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
hardware of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0884] At the operation 2208, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the operating
system of the real machine. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12, 13. Effect of
content acceptability determination engine 106 may transfer data
received from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12, 13. FIG.
1B illustrates virtual machines 11, 12, 13 encompassing a virtual
machine representation of real machine 130, post (e.g. subsequent
to) activation of Link 1, Link 2, and Link 3, respectively (e.g.,
as at least a part of real machine 130 would exist had link 1, link
2, and/or link 3 actually been traversed on real machine 130). FIG.
1B also illustrates virtual machine 11 including a virtual machine
representation of an operating system (e.g., a state of an
operating system and/or network operating system) of the real
machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
e.g. Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or a
network operating system (e.g., the Internet Operating System
available from Cisco Technology, Inc. Netware.RTM. available from
Novell, Inc., and/or Solaris available from Sun Microsystems,
Inc.). An example of determining an acceptability of an effect of
the content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of an operating system of the
real machine include determining whether a portion of the operating
system (e.g. Microsoft Vista) on for example, virtual machine 12
has been disabled after loading at least a portion of the data
contained in Link 2.
[0885] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the operating system of the real machine
may also include determining an acceptability of an effect of the
content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of the operating system of the
real machine on a virtual machine representation of at least a
portion of the operating system of a real machine generated by, for
example, virtual machine 11. FIG. 1C illustrates a partial
follow-on operational view of real machine 130 (e.g., a desktop,
notebook, or other type computing system) in which at least a
portion of system 100 (FIG. 1A) has been implemented (e.g., a
follow-on operational view of the systems/methods illustrated as in
FIG. 1B). Specifically, FIG. 1C illustrates a drill-down view of an
example of the virtual machine 11 including a virtual machine
representation of the content of the real machine 130 post
activation of Link 1 (e.g., a drill-down on the systems/methods
shown/described in relation to FIG. 1B). In this drill down
example, depicted is the virtual machine representation of the
content of the real machine 130 post activation of Link 1.
[0886] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0887] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link I (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 10). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
operating system (e.g. Linux) of the real machine 130 post
sequential activation of Link 1 then Link 4, a virtual machine
representation of an operating system (e.g. Mac OS/X) of the real
machine 130 post sequential activation of Link 1 then Link 5, and a
virtual machine representation of the operating system (e.g. GNU,
Berkeley Software Distribution) of the real machine 130 post
sequential activation of Link 1 then Link 6 (e.g., as such might
appear after activation of a link installed by a rootkit via
malware/spyware). A determination of an acceptability of an effect
of the content of data on the operating system of the real machine
made on virtual machine 21 may include determining whether or not a
rootkit has been installed onto virtual machine 21. Virtual machine
21 may communicate a determination of acceptability of an effect of
the content of data on a virtual machine representation of at least
a portion of operating system of the real machine made on virtual
machine 21 to virtual machine 11, which may communicate the
acceptability of an effect of the content of data determination to
the virtual machine module 118 (FIG. 1A) for communication to the
Effect of content acceptability determination engine 106 (FIG.
1A).
[0888] FIG. 135 illustrates alternative embodiments of the example
operational flow 200D of FIG. 114 where the providing at least one
data display option operation 230 may include at least one
additional operation. Additional operations may include an
operation 2302, an operation 2304, and/or an operation 2306.
[0889] At the operation 2302, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least a part of a computing device. FIG.
1D illustrates real machine 130 including at least a part of a
computing device 132. The computing device 132 may be any device
capable of processing one or more programming instructions. For
example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[0890] At the operation 2304, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
may spawn virtual machines 11, 12, 13 that may be virtual machine
representations of at least a part of real machine 130. Real
machine 130 may include at least one peripheral device. For
instance, FIG. 1D illustrates real machine 130 including at least
one peripheral device 134-146. FIG. 1D illustrates a representative
view of an implementation of real machine 130 (e.g., a desktop,
notebook, or other type computing system, and/or one or more
peripheral devices) in which all/part of system 100 may be
implemented. FIG. 1D illustrates that implementations of real
machine 130 may include all/part of computing device 132 and/or
all/part of one or one or more peripherals associated computing
device 132.
[0891] At the operation 2306, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a part of a real machine having one or more end-user
specified preferences includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 may spawn virtual machines 11, 12, 13
that may be virtual machine representations of at least a part of
real machine 130. Real machine 130 may include at least one
peripheral device. For instance, FIG. 1D illustrates a real machine
may also include at least a portion of one or more peripheral
devices connected/connectable (e.g., via wired, waveguide, or
wireless connections) to real machine 130. Peripheral devices may
include one or more printers 134, one or more fax machines 136, one
or more peripheral memory devices 138 (e.g., flash drive, memory
stick), one or more network adapters 139 (e.g., wired or wireless
network adapters), one or more music players 140, one or more
cellular telephones 142, one or more data acquisition devices 144
(e.g. robots) and/or one or more device actuators 146 (e.g., an
hydraulic arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
Application Ser. No. 12/154,436 (1206-003-007A2-000001)
[0892] FIG. 136 illustrates an operational flow 200E which includes
an operation 210 for retrieving at least a portion of data from a
data source (e.g. a computer accessible from the internet). For
example, FIG. 1A illustrates a data retriever engine 102. Data
retriever engine may retrieve (e.g. download) data 110 (e.g. a web
page) from a data source such as a computer accessible from the
internet. Specifically, data 110 may be web content retrieved from
the World Wide Web via a computing device accessible from the
internet. For example, data retriever engine 102 may set a URL and
add a query string value to the URL. Data retriever engine 102 may
then make a request to the URL and scan the response received from
the URL. Data 110 may be a web site or web page containing one or
more links to additional web sites, such as shown, for example, in
FIG. 1B and/or FIG. 1C. Data 110 may in some instances be textual,
a two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content.
[0893] Then, operation 220 illustrates determining a content of the
data. FIG. 1A illustrates a data content determination engine 104.
Data content determination engine 104 may determine the content
(e.g. text, audio, video, etc.) of the data 110 retrieved from the
data source by the data retriever engine 102. For example, FIG. 1A
illustrates that the data content determination engine 104 may
include a database examination engine 112, a data transverser
engine 114, and a local data examination engine 116. A database
examination engine 112 may examine (e.g. scan) a database (e.g.
information retrieved from a storage server) of known data (e.g.
web links) and compare the known data to the data 110 to determine
data content (e.g. data types such as text, image, audio and/or
video content). Additionally, database examination engine 112 may
compare a portion of data 110 (e.g. a data packet header) against a
database including a collection of data broken down into its
respective components (e.g. header, body). If the comparison yields
a reasonable match, the data type may be determined. Data content
determination may be transmitted from the database examination
engine 112 to the data content determination engine 104.
[0894] A data transverser engine 114 may traverse (e.g. parse) at
least a portion of the data (e.g. a portion of a web page) to
determine data content (e.g. an image or video) within the portion
of the data. Data traversal may occur in real time (e.g.
simultaneously as data is loading). Data content determination may
be transmitted from the data transverser engine 114 to the data
content determination engine 104.
[0895] A local data examination engine 116 may locally (e.g. on the
real machine 130) examine (e.g. analyze) at least a portion of the
data (e.g. data packets) to determine data content (e.g. an audio
file). For instance, local data examination engine 116 may view an
amount of html source code to locate markers signifying the type of
data content. Data content determination may be transmitted from
the local data examination engine 116 to the data content
determination engine 104. Data content determination engine 104 may
transmit a data content determination to the Effect of content
acceptability determination engine 106. The content of the data 110
may be any textual, audible, or visual content loaded or displayed
after the data is retrieved by the data retriever engine 102. For
instance, the content of the data 110 may be a web page comprising
text, sound, and/or an image, a link to a web page, a video or any
combination of text, sound, images, links to web pages, and
videos.
[0896] Then, operation 230 illustrates determining an acceptability
of an effect of the content of the data at least in part via a
virtual machine representation of at least a part of a real machine
having one or more end-user specified preferences. FIG. 1A
illustrates an Effect of content acceptability determination engine
106. Effect of content acceptability determination engine 106 may
receive data and an associated data content determination (e.g.
data is an audio file) from data content determination engine 104
post retrieval of data by data retriever engine 102 and transfer of
retrieved data to data content determination engine 106. Effect of
content acceptability determination engine 106 (FIG. 1A) may
utilize, for example, virtual machine 12 (FIG. 1A) spawned by
virtual machine module 118 to determine whether data associated
with Link 2 would result in a change in the operating system of
real machine 130 contra to user preferences regarding the operating
system as reflected by user preference database 120.
[0897] Then, operation 240 illustrates providing at least one data
display option based on the determining acceptability of the effect
of the content of the data. FIG. 1A illustrates a data provider
engine 108. Data provider engine 108 may be in communication with
Effect of content acceptability determination engine 106, which may
receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
post retrieval of data by data retriever engine 102 and transfer of
retrieved data to data content determination engine 104. Effect of
content acceptability determination engine 106 may transfer at
least effect of content acceptability determination to the data
provider engine 108 to provide at least one data display option. In
one example, data provider engine 108 (FIG. 1A) provides data via
placing the data on a visual display, where the content is such
that it meets one or more thresholds associated with the effect of
content acceptability determination. Provided data may be a list of
web links, a web page, or other data that either have been deemed
acceptable by effect of content acceptability determination engine
106 or that have been modified (e.g., obfuscated), such as by data
modification engine 122, such that the to-be-displayed content is
judged acceptable under user preferences. Provided data may be
modified via the data modification engine 122. For instance,
provided data may be obfuscated via the data obfuscation engine 124
(e.g., at least a portion of the displayed data may be blurred out
or disabled), or provided data may be anonymized via the data
anonymization engine 126 (e.g., at least a portion of the data may
be deleted entirely). Data content provider engine 108 (FIG. 1A)
may receive at least one display instruction (e.g. OK to display
links 1 and 2) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, each of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of content acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, and/or 13. Such instruction may include
an instruction to the data content provider engine 108 to prevent
the data content provider engine 108 from displaying data that may
configure a hardware profile of real machine 130 counter to
anti-viral settings stored in the user preference database 120
(FIG. 1A), or an instruction to the data content provider engine
108 to prevent the data content provider engine 108 from displaying
data that may configure an operating system of real machine 130
counter to a previous operating system of the real machine (130)
(e.g. determine if a rootkit has been installed).
[0898] FIG. 137 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[0899] Operation 302 illustrates examining a database of known data
for data information. Continuing the example above, data content
determination engine 104 (FIG. 1A) may receive data 110 retrieved
from a data source by the data retriever engine 102 and communicate
data 110 to the database examination engine 112. Database
examination engine 112 may be configured to examine a database of
data provided, for example, by a data provider service or a
database of data stored on a real machine 130. For instance, a
database may include a list of links viewed by a user or
pre-approved by a user based on one or more user-specified
preferences, such as links from a specific source of information
(e.g., the Roman Catholic Church). Database examination engine 112
may communicate the results of a database examination to the data
content determination engine 104.
[0900] Operation 304 illustrates traversing data in real time.
Continuing the example above, database transverser engine 114 (FIG.
1A) examines data received from the data content engine 104
following retrieval of data from the data retriever engine 102.
Data transverser engine 114 may be configured to scan the data 110
to determine a data content type (e.g. an image, a video or an
audio file). Database transverser engine 114 may communicate the
results of a data traversal to the data content determination
engine 104.
[0901] Operation 306 illustrates locally examining data. For
instance, continuing the example above, data content determination
engine 104 (FIG. 1A) may receive data 110 retrieved from a data
source (e.g. a computer accessible through the interne) by the data
retriever engine 102 and communicate data 110 to the local data
examination engine 116. The local examination engine 116 may
examine the data 110 on the real machine 130 at the location of the
real machine 130 (e.g. executed on a subsystem within the real
machine) to determine a data content type (e.g. a downloadable
software program). Local data examination engine 116 may
communicate the results of a local data examination to the data
content determination engine 104.
[0902] FIG. 138 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, an operation 406,
an operation 408, and/or an operation 410.
[0903] Operation 402 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13. Each of
virtual machines 11, 12, and/or 13 may examine (e.g. scan) at least
a portion of data (e.g. an imbedded link on a webpage) to determine
if the data references additional data (e.g. one or more additional
links). Additional data may be a web page comprising text and/or an
image, a link to a web page, a video or any combination of text,
images, links to web pages, or videos. Virtual machines 11, 12
and/or 13 may traverse additional data to determine an
acceptability of an effect of the data content. Effect of content
acceptability determination may be communicated to Effect of
content acceptability determination engine 106 (FIG. 1A) that may
communicate an effect of content acceptability determination to a
data provider engine 108 (FIG. 1A).
[0904] Further, operation 404 illustrates determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine having one or more end-user specified preferences by
determining whether data references additional data when loading.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
Any of virtual machines 11, 12 and/or 13 may examine the data in
real time as it loads onto the virtual machine 11, 12 and/or 13.
For instance, if a link to a webpage immediately (e.g. as soon as
the link is activated) references an additional link (e.g. to
redirect a user), a virtual machine 11, 12 and/or 13 may determine
that such a reference to an additional link has been made. Virtual
machines 11, 12 and/or 13 may determine whether data references
additional data at any time when the data is loading. Effect of
content acceptability determination engine 106 (FIG. 1A) may
communicate an effect of content acceptability determination to a
data provider engine 108 (FIG. 1A).
[0905] Operation 406 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by issuing a request to
a remote computer for additional data information. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13. The data of
an additional link or links may be examined by at least one of
virtual machines 11, 12 and/or 13 issuing a request to receive
additional data information from a remote computer (e.g. a computer
at a geographically distinct location).
[0906] Operation 408 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences by examining a copy of
data from a location geographically distinct from a location of the
data. Continuing the example above, FIG. 1A illustrates the Effect
of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102 and
communication of retrieved data to data content determination
engine 104. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12 and/or 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. FIG. 1B illustrates virtual machines 11,
12 and/or 13. The data of an additional link or links may be
examined by at least one of virtual machines 11, 12 and/or 13
issuing a request to a remote computer to examine additional data
information at the remote computer (e.g. a computer at a
geographically distinct location).
[0907] Further, operation 410 illustrates generating a substantial
duplicate of at least a part of a real machine at a location
geographically distinct from a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
For instance, a virtual machine 11, 12 and/or 13 of the real
machine may be located at a geographically distinct location such
as a remote server, or a remote system configured duplicate data
from the real machine 130 and to receive and examine real machine
information transferred to the remote server or remote system.
System 100 may include any number of communication modules (not
shown) configured to communicate over local or remote communication
channels.
[0908] FIG. 139 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 502, an operation 504, an operation 506,
and/or an operation 508.
[0909] Operation 502 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of a substantial portion of a real machine
having one or more end-user specified preferences. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
For instance, FIG. 1B illustrates virtual machines 11, 12, 14
including a virtual machine representation of content of the real
machine 130, software or the real machine 130, hardware of the real
machine 130, and an operating system of the real machine 130.
Virtual machines 11, 12 and/or 13 may include most or all of at
least one of the content of the real machine 130 (e.g. a
substantial portion of the text, image, audio, and video files of
the real machine), software of the real machine 130 (e.g. a
substantial portion of any program or suite of programs installed
on the real machine), hardware of the real machine 130 (a
substantial portion of the circuitry comprising the real machine),
and/or an operating system of the real machine 130 (e.g. a
substantial portion of a Windows.RTM. operating system installed on
the real machine).
[0910] Operation 504 illustrates for determining an acceptability
of an effect of the content of the data at least in part via a
virtual machine representation of at least a portion of data on a
real machine having one or more end-user specified preferences.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 including a
virtual machine representation of content of the real machine 130,
a virtual machine representation of software of the real machine
130, a virtual machine representation of hardware of the real
machine 130, and/or a virtual machine representation of an
operating system of the real machine 130 post activation of link 1,
link 2, and link 3 of data 110 (e.g., a Web page) resident on real
machine 130. These post activation states are examples of effects
of the content of data 110. As additional examples, virtual
machines 11, 12 and/or 13 may include at least a portion of at
least one of the content of the real machine 130 (e.g. the video
files of a real machine), software or the real machine 130 (e.g.
iTunes), hardware of the real machine 130 (e.g. a data processor),
and/or an operating system of the real machine 130 (e.g. a portion
of Netware.RTM.).
[0911] Operation 506 illustrates determining an acceptability of an
effect of data at least in part via a virtual machine
representation operating at a location of the data. Continuing the
example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B further illustrates virtual machines 11, 12 and/or 13. In
one implementation, any of virtual machines 11, 12 and/or 13 may be
generated on the real machine 130 (e.g. as a subsystem of real
machine 130).
[0912] Operation 508 illustrates determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation operating at a location geographically
distinct from a location of the data. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. FIG. 1B further
illustrates virtual machines 11, 12 and/or 13. In one
implementation, any of virtual machines 11, 12 and/or 13 may be
generated on a remote server, remote operating system or otherwise
geographically distinct location with respect to the real machine
130.
[0913] FIG. 140 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 602, an operation 604, an operation 606,
and/or an operation 608.
[0914] Operation 602 illustrates determining an acceptability of an
effect of the content of the data on at least two virtual machine
representations of at least a part of a real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. FIG. 1B illustrates
virtual machines 11, 12, and 13. At least two of virtual machines
11, 12 and/or 13 may include virtual machine representations of at
least a portion of software, hardware and an operating system of
the real machine 130.
[0915] Further, operation 604 illustrates determining an
acceptability of an effect of the content of the data on at least
two virtual machine representations of at least a part of a real
machine having one or more end-user specified preferences at least
one of the at least two virtual machine representations operating
on a separate operating system. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. For instance, a virtual machine 11, 12
and/or 13 (FIG. 1A) may individually mimic one of Windows XP,
Windows 2000 with SQL 2000 and SharePoint Server 2003, Windows 2003
with Exchange 2003, an Apple operating system (e.g., MAC OS 9, OS X
Leopard), or Red Hat Linux with Apache. Further, each virtual
machine 11, 12 and/or 13 may mimic a different operating system
(e.g., virtual machine 11 may mimic Windows XP, virtual machine 12
may mimic Windows 2000 and virtual machine 13 may mimic Red Hat
Linux and so on). Operating system may be any software configured
to manage the sharing of the resources of a computer, process
system data and user inputs, and respond to user inputs by
allocating and managing tasks and internal system resources.
Operating system may be, for example Microsoft Windows.RTM. 2000,
XP, or Vista available from Microsoft Corporation of Redmond,
Wash., Mac OS X, Linux or any other operating system.
[0916] Operation 606 illustrates determining an acceptability of an
effect of the content of the data on at least two virtual machine
representations of at least a part of a real machine having one or
more end-user specified preferences, at least one of the at least
two virtual machine representations operating on a separate core of
a system comprising at least two cores. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. As illustrated in
FIGS. 1B and 1C, each of virtual machine 11, virtual machine 12,
virtual machine 13, virtual machine 21, virtual machine 22, and
virtual machine 23 may operate on an individual core 11, 12 and/or
13, 31, 32, 33, respectively, of a multi-core processor, or virtual
machine 11 may run on one core and virtual machines 12 and/or 13
may run on the other core of a dual core processor such as an
Intel.RTM. dual core processor and so on. The multi-core processor
may include a plurality of processor cores packaged in one
processor package. The term core as used herein may refer, for
example, to a single processor of a multiprocessor system, or to a
processor core of a multi-core processor. Multi-core processor may
be utilized as portable computers such as laptop computers,
personal digital assistants, or desktop computers, or servers, or
another form of processor based system. Combinations of these types
of platforms may be present. The multi-core system may include a
multi-core processor, each core comprising a separate address
space, and having internal to that address space.
[0917] Operation 608, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location of the data. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106. Effect of content acceptability
determination engine 106 may receive a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102 and communication of retrieved data to
data content determination engine 104. FIG. 1A further illustrates
the Effect of content acceptability determination engine 106
further including a virtual machine module 118 and a user
preference database 120. Virtual machine module 118 includes
virtual machines 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may transfer data received from data
content determination engine 104 following a determination of data
content. Effect of content acceptability determination engine 106
may transfer the data and associated data content determination to
the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. Each of virtual
machines 11, 12 and/or 13 may operate on a separate operating
system at a location of the data (e.g. executed on a subsystem,
such as the virtual machine module 118 (FIG. A) including a
plurality of virtual machines 11, 12 and/or 13 (FIG. 1B) within the
real machine 130).
[0918] FIG. 141 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 702, an operation 704, an operation 706,
and/or an operation 708.
[0919] Operation 702 illustrates determining a state change of a
virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer the
data and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. A state change (e.g. a decrease
in memory) of virtual machine 11, 12 and/or 13 (FIG. 1B) may be
determined by a component of virtual machine 11, 12 and/or 13
measuring a characteristic of the virtual machine representation of
the content, software, hardware or operating system of the real
machine 130 before and after the at least a portion of data has
loaded. For instance, a state change may be measured after a search
result containing a plurality of web links has loaded and at least
one web link has been activated.
[0920] Operation 704 illustrates determining a state of a virtual
machine representation prior to loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12 and/or
13. Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. Virtual machine 11,
12 and/or 13 may determine a state of at least one component (e.g.
the hardware) of the virtual machine prior to activation (e.g.
before) of a link. Virtual machine state may be representative of a
state for all or at least a portion of the components (e.g.
content, software, hardware, operating system) of the real machine
130 represented by the virtual machine 11, 12 and/or 13. For
instance, a virtual machine 11, 12 and/or 13 may be determined to
be free of viruses, an amount of virtual machine memory may be
measured, or a processing speed of the virtual machine 11, 12
and/or 13 may be determined. Virtual machines 11, 12 and/or 13 may
contain a diagnostic application configured to analyze virtual
machine performance and contents.
[0921] Further, operation 706 illustrates determining a state of a
virtual machine after loading at least a portion of data.
Continuing the example above, FIG. 1A illustrates the Effect of
content acceptability determination engine 106 including a virtual
machine module 118 further including virtual machines 11, 12 and/or
13. Upon receiving data and a data content determination from data
content determination engine 104 post retrieval of data by data
retriever engine 102, Effect of content acceptability determination
engine 106 may transfer the data and associated data content
determination to virtual machine module 118. Virtual machine module
118 may spawn at least one virtual machine 11, 12, and/or 13 and
transfer the data and associated data content determination to at
least one of virtual machines 11, 12 and/or 13. Virtual machine 11,
12 and/or 13 may determine a state of at least one component (e.g.
the hardware) of the virtual machine subsequent to (e.g. after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by the virtual machine 11, 12 and/or 13 after at least
a portion of the data has loaded. For instance, a virtual machine
11, 12 and/or 13 may be determined to contain a virus, an amount of
virtual machine memory may be measured, or a processing speed of
the virtual machine 11, 12 and/or 13 may be determined. Virtual
machine 11, 12 and/or 13 may be examined to determine, for example,
if a virus or any other undesired software is present on the
machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[0922] Operation 708 illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. An undesirable state change may be
determined by examining the changes to the virtual machine 11, 12
and/or 13 and comparing the state change of the virtual machine 11,
12 and/or 13 to user preference database information spawned on
virtual machines 11, 12 and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. 1A)
onto virtual machines 11, 12 and/or 13. A state change may include
any undesirable state changes such as a decrease in memory or
processing speed and/or the presence of a virus or other
undesirable software after at least a portion of the data has
loaded. Undesirable state changes may further include an
undesirable transfer of information located on the virtual machine
11, 12 and/or 13 to an external location, an undesirable transfer
of data onto the virtual machine 11, 12 and/or 13 from an external
location after at least a portion of the data has loaded on the
virtual machine 11, 12 and/or 13 that may result in an undesired
change in the state of content, software, hardware or an operating
system of the real machine 130 and/or an undesirable transfer of
data onto the virtual machine 11, 12 and/or 13 where at least a
portion of the transferred data may be found objectionable when
viewed by a user 10.
[0923] FIG. 142 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 802, an operation 804, an operation 806, an
operation 808, and/or an operation 810.
[0924] Operation 802 illustrates determining an acceptability of an
effect of the content of the data in response to at least one user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12 and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
An undesirable state change may be determined by examining the
changes to the virtual machine 11, 12 and/or 13 and comparing the
state change of the virtual machine 11, 12 and/or 13 to user
preference database information spawned on virtual machines 11, 12
and/or 13 by a transfer of user preference database information
from the user preference database 120 (FIG. 1A) to the virtual
machine module 118 (FIG. 1A) which spawns a copy of at least a
portion of the user preference database 120 (FIG. 1A) onto virtual
machines 11, 12 and/or 13. User preference database 120 may include
at least one end-user specified preference relating to at least one
of content, software, hardware and/or an operating system of a real
machine 130. At least one of virtual machines 11, 12 and/or 13 may
determine an acceptability of an effect of the content of the data
based on at least one user setting contained in a user preference
database at least a portion of which may be spawned onto virtual
machines 11, 12 and/or 13 via virtual machine module 118 (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a setting established by a
user such as a political or cultural preference setting). Further
examples of user preferences include specific religion or lifestyle
preference, such as "return only links relating to Roman
Catholicism" or "return only links relating to a vegan lifestyle"
that may be stored in the real machine 130. User-specific
preference may also relate to user information safety or computer
safety, such as "do not display links requesting information from
my computer," or "do not display links that transfer viruses onto
my computer."
[0925] Operation 804 illustrates determining an acceptability of an
effect of the content of the data in response to a personal user
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12 and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
User preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12 and/or 13. Virtual machines 11, 12 and/or 13 may compare the
data received from the virtual machine module to a personal user
setting (e.g. "show only automobile related data") contained in
user preference database information spawned on virtual machines
11, 12 and/or 13. User preference database 120 may include at least
one personal user setting relating to at least one of content,
software, hardware and/or an operating system of a real machine
130. Personal user setting may be a setting input by a user that is
personal to the user, such as an information security level, a
content filter level, or a personal desirability setting such as
"show only non-religious data" or "show only automobile related
data."
[0926] Further, operation 806 illustrates determining an
acceptability of an effect of the content of the data in response
to a peer user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module to
a peer user setting contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. User
preference database 120 may include at least one peer user setting
relating to at least one of content, software, hardware and/or an
operating system of a real machine 130. Peer user setting may be a
setting input by a user that is determined by a peer group, such as
a peer group determined information security level such as "display
only 100 percent secure websites", a peer group determined data
filter level such as "filter 100% of obscene data", or a peer group
desirability setting such as "show only classical music related
data" or "show only knitting related data."
[0927] Additionally, operation 808 illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate user setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a corporate user setting contained in user preference
database information spawned on virtual machines 11, 12 and/or 13.
User preference database 120 may include at least one corporate
user setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130.
Corporate user setting may be a setting input by a corporation that
is determined to the corporation, such as a corporate desirability
setting such as "show only real-estate related data" or "show only
agricultural related data."
[0928] Further, operation 810 illustrates determining an
acceptability of an effect of the content of the data in response
to a work safety user setting. Continuing the example above, FIG.
1A illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a work safety user setting contained in user preference
database information spawned on virtual machines 11, 12 and/or 13.
User preference database 120 may include at least one work safety
user setting relating to at least one of content, software,
hardware and/or an operating system of a real machine 130. Thus, in
one specific example, a webpage or website data may be determined
to be determined to be displayable if the data satisfies a work
safety user setting such as a corporate information security level,
corporate user setting, or a corporate information content filter
level corporate user setting.
[0929] FIG. 143 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 902, an operation 904, an operation 906, an
operation 908, an operation 910, and/or an operation 912.
[0930] Operation 902 illustrates determining an acceptability of an
effect of the content of the data in response to a desirability
setting. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106 including
a virtual machine module 118 further including virtual machines 11,
12 and/or 13. Upon receiving data and a data content determination
from data content determination engine 104 post retrieval of data
by data retriever engine 102, Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to virtual machine module 118. Virtual
machine module 118 may spawn at least one virtual machine 11, 12,
and/or 13 and transfer data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
User preference database information stored in the user preference
database 120 (FIG. 1A) may be transferred to the virtual machine
module 118 (FIG. 1A), which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto virtual machines
11, 12 and/or 13. Virtual machines 11, 12 and/or 13 may compare the
data received from the virtual machine module 118 to a desirability
setting (e.g., does a website contain only images, text, audio or
visual data suitable for viewing by a user based on a desirability
setting established by a user such as a desire to view only
non-obscene material) contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. User
preference database 120 may include at least one desirability
setting relating to at least one of content, software, hardware
and/or an operating system of a real machine 130.
[0931] Operation 904 illustrates determining an acceptability of an
effect of the content of the data in response to a religious
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a religious desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a religious desirability setting
established by a user such as a desire to view only Hindu material)
contained in user preference database information spawned on
virtual machines 11, 12 and/or 13. A religious desirability setting
may be include any setting regarding a major, minor, or other
religion such as Christianity, Judaism, Islam, Hinduism, and so
on.
[0932] Operation 906 illustrates determining an acceptability of an
effect of the content of the data in response to a political
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a political desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a political desirability setting
established by a user such as a desire to view only Democratic
Party material) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. A political
desirability setting may include any setting regarding a political
party or affiliation (e.g. Republican, Democratic, Libertarian,
Green Party, etc.).
[0933] Operation 908 illustrates determining an acceptability of an
effect of the content of the data in response to a cultural
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a cultural desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a cultural desirability setting
established by a user such as a desire to view only materials
regarding early Mayan civilization) contained in user preference
database information spawned on virtual machines 11, 12 and/or 13.
A cultural desirability setting may include any culturally related
information such as a religious, ethnic, regional, or heritage
based cultural desirability setting or any other cultural
desirability setting.
[0934] Operation 910 illustrates determining an acceptability of an
effect of the content of the data in response to a theme related
desirability setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a theme related desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a theme related desirability setting
established by a user such as a desire to view only materials
regarding collectible stamps) contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. A theme
related desirability setting may include any theme related
information, such as information relating to cars, fashion,
electronics, sports, hobbies, collector's items, or any theme or
category that may be of interest to a user.
[0935] Operation 912 illustrates determining an acceptability of an
effect of the content of the data in response to an age
appropriateness desirability setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to an age appropriateness
desirability setting (e.g., does a website contain only images,
text, audio or visual data suitable for viewing by a user based on
an age appropriateness desirability setting established by a user
such as a desire to view only materials given a PG or lower rating
as determined by the Motion Picture of America Association film
rating system) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. An age
appropriateness desirability setting may include any age
appropriate setting, such as a rating threshold or a profanity
threshold.
[0936] FIG. 144 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 1002, an operation 1004, an operation 1006,
and/or an operation 1008.
[0937] Operation 1002 illustrates determining an acceptability of
an effect of the content of the data in response to at least one
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a privacy related setting (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a privacy related setting established by a user) contained
in user preference database information spawned on virtual machines
11, 12 and/or 13. A privacy related setting may include any privacy
related settings (e.g., does a website contain only data that will
not request information from my computer or allow others to view
personal information saved on my computer).
[0938] Operation 1004 illustrates determining an acceptability of
an effect of the content of the data in response to a user specific
privacy related setting. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to a user specific privacy related setting (e.g., will a
website request specific information about the user such as name,
address, telephone number) contained in user preference database
information spawned on virtual machines 11, 12 and/or 13. A user
specific privacy related setting may include any user specific
privacy related settings (e.g., a setting relating to a user's
biographical information or financial information).
[0939] Further, operation 1006 illustrates determining an
acceptability of an effect of the content of the data in response
to a group privacy related setting. Continuing the example above,
FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to a group privacy related
setting (e.g., will a website request information about an
organization such as name, address, telephone number) contained in
user preference database information spawned on virtual machines
11, 12 and/or 13. A group privacy related setting may include any
group privacy related settings (e.g., a setting relating to a
group's membership). Group privacy related setting may be any
setting established by a group such as a work group (e.g. employees
of a company), a peer group (e.g., members of a book club), or a
family group (e.g. members of family unit) privacy related
setting.
[0940] Further, operation 1008 illustrates determining an
acceptability of an effect of the content of the data in response
to a corporate privacy related setting. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to a corporate privacy related
setting (e.g., will a website request information about a
corporation such as data stored on a real machine belonging to the
corporation) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. Corporate privacy
related setting may be determined by a corporate issued privacy
manual, or other such document or mandate set forth by officers of
a corporation.
[0941] FIG. 145 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data operation 230 may include
at least one additional operation. Additional operations may
include an operation 1102, an operation 1104, an operation 1106,
and/or an operation 1108.
[0942] Operation 1102 illustrates determining an acceptability of
an effect of the content of the data in response to a type of
transmitted user information. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. Virtual machines 11, 12 and/or
13 may compare the data received from the virtual machine module
118 to at least one acceptable type of transmitted user information
setting (e.g., do not return links that will transmit my e-mail
address, home address or telephone number to an external location)
contained in user preference database information spawned on
virtual machines 11, 12 and/or 13. Acceptable type of transmitted
user information setting may be determined by a user 10 (FIG. 1B).
For instance, acceptability of the effect of the data may be
determined in response to whether or not private user information,
such as credit card numbers, bank accounts, personal identification
information or any other personal user information may be
transmitted to a location external to the real machine by selecting
the link.
[0943] Further, operation 1104 illustrates determining an
acceptability of an effect of the content of the data in response
to a type of captured user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to at least one acceptable type
of captured user information setting (e.g., do not return links
that will capture my e-mail address, home address or telephone
number) contained in user preference database information spawned
on virtual machines 11, 12 and/or 13. Acceptable type of captured
user information setting may be determined by a user 10 (FIG. 1B).
For instance, acceptability of the effect of the data may be
determined in response to whether or not private user information,
such as credit card numbers, bank accounts, personal identification
information or any other personal user information may be captured
by a machine located at a location external to the real machine by
selecting the link.
[0944] Further, operation 1106 illustrates determining an
acceptability of an effect of the content of the data in response
to a type of exposed user information. Continuing the example
above, FIG. 1A illustrates the Effect of content acceptability
determination engine 106 including a virtual machine module 118
further including virtual machines 11, 12 and/or 13. Upon receiving
data and a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102, Effect of content acceptability determination engine
106 may transfer the data and associated data content determination
to virtual machine module 118. Virtual machine module 118 may spawn
at least one virtual machine 11, 12, and/or 13 and transfer data
and associated data content determination to at least one of
virtual machines 11, 12 and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13.
Virtual machines 11, 12 and/or 13 may compare the data received
from the virtual machine module 118 to at least one acceptable type
of exposed user information setting (e.g., do not return links that
will expose personal financial information stored on the real
machine 130) contained in user preference database information
spawned on virtual machines 11, 12 and/or 13. Acceptable type of
exposed user information setting may be determined by a user 10
(FIG. 1B). For instance, acceptability of the effect of the data
may be determined in response to whether or not private user
information, such as credit card numbers, hank accounts, personal
identification information or any other personal user information
may be exposed to a machine located at a location external to the
real machine by selecting the link.
[0945] Operation 1108 illustrates determining an acceptability of
an effect of the content of the data in response to visually
examining a data image. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. To visually examine a data image, a virtual machine
11, 12 and/or 13 may include an image scanning module. Visually
examining the data image may include, for example, color analysis,
pattern-matching, pattern-recognition, or any other technique for
recognizing a particular image or type of image.
[0946] FIG. 146 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the determining an
acceptability of the effect of the data of the data operation 230
may include at least one additional operation. Additional
operations may include an operation 1202.
[0947] Operation 1202, illustrates determining an acceptability of
an effect of the content of the data on at least two virtual
machine representations of at least a part of a real machine having
one or more end-user specified preferences, at least one of the at
least two virtual machine representations operating on a separate
operating system at a location geographically distinct from a
location of the data. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106 including a virtual machine module 118 further including
virtual machines 11, 12 and/or 13. Upon receiving data and a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102, Effect of
content acceptability determination engine 106 may transfer the
data and associated data content determination to virtual machine
module 118. Virtual machine module 118 may spawn at least one
virtual machine 11, 12, and/or 13 and transfer data and associated
data content determination to at least one of virtual machines 11,
12 and/or 13. User preference database information stored in the
user preference database 120 (FIG. 1A) may be transferred to the
virtual machine module 118 (FIG. 1A), which spawns a copy of at
least a portion of the user preference database 120 (FIG. 1A) onto
virtual machines 11, 12 and/or 13. At least two virtual machines,
for example virtual machines 12 and/or 13 may be virtual machines
operating at geographically distinct location such as a remote
server, or a remote system configured to receive and examine real
machine information transferred to the remote system and duplicate
data from the real machine 130. In some instances, each virtual
machine may be generated on one or more separate cores of a
multi-core processor.
[0948] FIG. 147 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1302, an operation 1304, an operation 1306, an operation
1308, and/or an operation 1310.
[0949] Operation 1302 illustrates providing a data display option
of displaying the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
video file) from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display the entire text of link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. Data content provider engine
108 may then display the data. Displayed data may be an unmodified
web page of text, images and/or video, or a web page including
links to additional web pages and may be displayed on a real
machine display such as a computer screen.
[0950] Operation 1304 illustrates providing a data display option
of not displaying the data. Continuing the example above, data
provider engine 108 (FIG. 1A) may be in communication with Effect
of content acceptability determination engine 106 (FIG. 1A), which
may receive data and an associated data content determination (e.g.
data is a video file) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of not
displaying at least a portion of the data. For instance, data
content provider engine 108 may receive at least one do not display
instruction (e.g. Do not display the text of link 1) from at least
one component of Effect of content acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may
include one or more instruction generating modules configured to
provide a do not display instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the do not display
instruction to the data content provider engine 108. The data
display option of not displaying the data may include a message
indicated why the data is not being displayed, or may be, for
example, a blank page displayed on a display of the real
machine.
[0951] Operation 1306 illustrates providing a data display option
of displaying a modified version of the data. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a portion of
the data. For instance, data content provider engine 108 may
receive at least one modify data instruction (e.g. display only
lines 1-10 of the text of link 1) from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a modify data
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the modify data instruction to the data content provider engine
108. The data content provider engine 108 may transmit the modify
data instruction to the data modification engine 122 for
modification of the data. Data modification engine may transmit the
modified data to the data content provider engine 108. Data content
provider engine 108 may then display the modified version of the
data. Displayed data may be a modified web page of text, a modified
image and/or a modified video, or a modified web page including
links to additional web pages. For instance, a webpage or website
may be displaying, but any obscenities on the web page or website
may replaced by non-obscene word alternatives.
[0952] Further, operation 1308 illustrates providing a data display
option of obfuscating an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of obfuscating (e.g. blurring) a
portion of the data (e.g. obscene photos). For instance, data
content provider engine 108 may receive at least one obfuscate data
instruction (e.g. display only non-obscene portions of the image in
link 1) from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12 and/or 13 may include one or more instruction
generating modules configured to provide an obfuscate data
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the obfuscate data instruction to the data content provider engine
108. The data content provider engine 108 may transmit the
obfuscate data instruction to the data modification engine 122
which may transmit the obfuscate data instruction to the data
obfuscation engine 124. Data obfuscation engine 124 may transmit
the obfuscated data to the data modification engine 122 for
transmission to the data content provider engine 108. Data content
provider engine 108 may then display the obfuscated version of the
data. For example, obfuscating logic may obfuscate restricted data
or imagery within a webpage or image. Obfuscation may include
blurring or blocking of the objectionable data portion.
[0953] Further, operation 1310 illustrates providing a data display
option of anonymizing an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination (e.g. data is a video file) from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of anonymizing (e.g. obscuring
source information) for a portion of the data (e.g. graphic
videos). For instance, data content provider engine 108 may receive
at least one anonymize data instruction (e.g. obscure source
information for portions of the video in link 1) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may
include one or more instruction generating modules configured to
provide an anonymize data instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the anonymize data
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the anonymize data
instruction to the data modification engine 122 which may transmit
the anonymize data instruction to the data anonymization engine
126. Data anonymization engine 126 may transmit the anonymized data
to the data modification engine 122 for transmission to the data
content provider engine 108. Data content provider engine 108 may
then display the anonymized version of the data. Anonymized data
may be data in which the original identity information of the data
is hidden, obscured, replaced, and/or otherwise modified.
[0954] FIG. 148 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1402, an operation 1404, an operation 1406, and/or an
operation 1408.
[0955] Operation 1402 illustrates providing a data display option
of removing, altering, or replacing an objectionable data portion.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an audio file)
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of removing, altering or
replacing an objectionable data portion (e.g. replacing profanity
with innocuous language) for a portion of the data (e.g. explicit
lyrics). For instance, data content provider engine 108 may receive
at least one alter, remove or replace instruction (e.g. obscure
source information for portions of the video in link 1) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a user preference
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may communicate the remove,
alter or replace data instruction to the data content provider
engine 108. The data content provider engine 108 may transmit the
anonymize data instruction to the data modification engine 122
which may then remove, alter or replace the data. Data modification
engine 122 may transmit the data containing removed, altered or
replaced portions to the data content provider engine 108. Data
content provider engine 108 may then display the data containing
removed, altered, or replaced portions. Thus, in one specific
example, a portion of a webpage produced by a search including data
relating to religions other than Catholicism may be removed from
the web page prior to display of the data on a real machine display
such as a computer screen.
[0956] Operation 1404 illustrates providing a data display option
of displaying a data portion consistent with at least one setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is text) from data
content determination engine 104 (FIG. 1A) post retrieval of data
by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one setting. For instance, data content provider
engine 108 may receive at least one display instruction (e.g. OK to
display only text consistent with a corporate established setting)
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12 and/or 13. Effect of content acceptability determination
engine 106 may communicate the display instruction to the data
content provider engine 108. If data needs to be modified to be
consistent with at least one setting, the data content provider
engine 108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108 (e.g., a setting such as recast all
text to large, and reformat a page consistent with the large text,
such as might be done for an individual having special vision
needs). Data content provider engine 108 may then display the data
consistent with the setting.
[0957] Further, operation 1406 illustrates providing a data display
option of displaying a data portion consistent with a privacy
related setting. Continuing the example above, data provider engine
108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data does
not contain spyware) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one privacy related
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g. OK to display webpage) from
at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a privacy related setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one privacy related setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data consistent with the privacy
related setting. For instance, a portion of a returned webpage
including data requesting private user information such as a user's
social security number or e-mail address may be removed from the
web page prior to display of the data on a computer screen. Further
specific examples include a webpage or website data may be
determined to be displayable if the data satisfies a setting such
as a privacy related setting such as a setting relating to a user's
biographical information or financial information, a webpage or
website data may be determined to be displayable if the data
satisfies a group privacy related setting such as a work group
(e.g. employees of a company), a peer group (e.g., members of a
book club), or a family group (e.g. members of family unit) privacy
related setting, or a webpage or website data may be determined to
be displayable if the data satisfies a privacy setting determined
by a corporation or other organization to maintain corporate or
organization privacy.
[0958] Further, operation 1408 illustrates providing a data display
option of displaying a data portion consistent with a user setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data does not contain
malware) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one user setting. For instance, data
content provider engine 108 may receive at least one display
instruction (e.g. OK to display webpage) from at least one
component of Effect of content acceptability determination engine
106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of content acceptability
determination engine 106 after a comparison of an activation of a
link to a user setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one user setting, the data content provider engine 108 may
transmit the modify data instruction to the data modification
engine 122 for modification of the data. Data modification engine
122 may transmit the modified data to the data content provider
engine 108. Data content provider engine 108 may then display the
data consistent with the user setting. Thus, a webpage or website
data may be determined to be displayable if the data satisfies a
user setting when the virtual machine 11, 12 and/or 13 compares the
data to the user setting. For instance, a portion of a webpage
produced by a search including non-English text may be removed from
the web page prior to display of the data on a computer screen.
Further, in one specific example, a webpage or website data may be
determined to be displayable if the data satisfies a peer user
setting, or a webpage or website data may be determined to be
displayable if the data satisfies, for instance, a corporate user
setting.
[0959] FIG. 149 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1502, and/or an operation 1504.
[0960] Operation 1502 illustrates providing a data display option
of displaying a data portion consistent with a desirability
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12 and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
desirability setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one desirability setting, the data content provider engine
108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
content provider engine 108. Data content provider engine 108 may
then display the data portion consistent with the desirability
setting. For instance, the data display option may be displaying on
a display of a real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[0961] Further, operation 1504 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is a
social networking site) from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
displaying data consistent with at least one workplace established
setting. For instance, data content provider engine 108 may receive
at least one display instruction (e.g. do not display data) from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace established setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace established setting,
the data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data portion consistent with the
workplace established setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with a workplace appropriateness desirability
setting such as "display only non-obscene data."
[0962] FIG. 150 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1602, an operation 1604, and/or an operation 1606.
[0963] Operation 1602 illustrates providing a data display option
of displaying a data portion consistent with a safety setting.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of content acceptability
determination engine 106 (FIG. 1A), which may receive data and an
associated data content determination (e.g. data is an image) from
data content determination engine 104 (FIG. 1A) post retrieval of
data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of displaying data consistent
with at least one safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
(e.g. OK to display image) from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of content acceptability determination engine 106
after a comparison of an activation of a link to a safety setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may communicate the display
instruction to the data content provider engine 108. If data needs
to be modified to be consistent with at least one safety setting,
the data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data content provider engine 108. Data content provider
engine 108 may then display the data portion consistent with the
safety setting. For instance, the data display option may be
displaying on a display of a real machine only a data portion
consistent with child safety setting such as "display only
non-violent data," or "display only ethnic and gender neutral
data."
[0964] Further, operation 1604 illustrates providing a data display
option of displaying a data portion consistent with a public safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination (e.g. data is an
image) from data content determination engine 104 (FIG. 1A) post
retrieval of data by data retriever engine 102 (FIG. 1A). Effect of
content acceptability determination engine 106 may transfer effect
of content acceptability determination to the data provider engine
108 to provide the data display option of displaying data
consistent with at least one desirability setting. For instance,
data content provider engine 108 may receive at least one display
instruction (e.g. OK to display image) from at least one component
of Effect of content acceptability determination engine 106 (FIG.
1A). Each of virtual machines 11, 12 and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
desirability setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or
13. Effect of content acceptability determination engine 106 may
communicate the display instruction to the data content provider
engine 108. If data needs to be modified to be consistent with at
least one public safety setting, the data content provider engine
108 may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data content
provider engine 108 may then display the data portion consistent
with the public safety setting. For instance, the data display
option may be displaying on a display of a real machine only a data
portion consistent with public safety setting such as "display only
non-confidential data."
[0965] Further, operation 1606 illustrates providing a data display
option of displaying a data portion consistent with a home safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one home safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a home safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one home safety setting, the data
content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the home safety setting. For instance,
the data display option may be displaying on a display of a real
machine only a data portion consistent with home safety setting
such as "okay to display private or confidential data."
[0966] FIG. 151 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1702, and/or an operation 1704.
[0967] Operation 1702 illustrates providing a data display option
of displaying a data portion consistent with a workplace safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a workplace safety setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one workplace safety setting, the
data content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a workplace
safety setting such as "display only non-personal data."
[0968] Further, operation 1704 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one child safety setting. For instance, data content
provider engine 108 may receive at least one display instruction
from at least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a child safety setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the display instruction to
the data content provider engine 108. If data needs to be modified
to be consistent with at least one child safety setting, the data
content provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data content provider engine 108 may then display the
data portion consistent with the child safety setting. For
instance, the data display option may be displaying on a display of
a real machine only a data portion consistent with a child safety
setting such as "display only non-violent data."
[0969] FIG. 152 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1802, an operation 1804, an operation 1806, and/or an
operation 1808.
[0970] Operation 1802 illustrates redirecting to alternative data a
user may be redirected to alternative data. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the redirect instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
[0971] Operation 1804 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a privacy related
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a privacy related setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a privacy related setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a privacy related setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a privacy related setting may include displaying a
different webpage including only information consistent with a
privacy related setting such as "display only links that do not
request e-mail addresses." Privacy related setting may be any
privacy related setting described above and may include any
additional privacy related settings.
[0972] Further, operation 1806 illustrates displaying alternative
data consistent with a customized user setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a customized user
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a customized user setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a customized user setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a customized user setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a customized user setting may include displaying a
different webpage including only information consistent with a
customized user setting such as "display only links containing
French text." Thus, in one specific example, a webpage or website
data may be determined to be displayable if the data satisfies a
customized user setting when the virtual machine 11, 12 and/or 13
compares the data to the customized user setting.
[0973] Further, operation 1808 illustrates displaying alternative
data consistent with a desirability setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a desirability
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a desirability setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a desirability setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a desirability setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
desirability setting may include displaying a different webpage
including only information consistent with a desirability setting
such as "display only links containing information relating to
art." Desirability setting may be any desirability setting
described above and may include any additional desirability
settings.
[0974] FIG. 153 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 1902, and/or an operation 1904.
[0975] Operation 1902 illustrates displaying alternative data
consistent with a workplace established setting. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of content acceptability determination
engine 106 (FIG. 1A), which may receive data and an associated data
content determination from data content determination engine 104
(FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.
1A). Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace
established setting (e.g. another website). For instance, data
content provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of content
acceptability determination engine 106 (FIG. 1A). Each of virtual
machines 11, 12 and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of content acceptability determination engine 106 after
a comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12 and/or 13. Effect of
content acceptability determination engine 106 may communicate the
redirect to alternative data consistent with a workplace
established setting instruction to the data content provider engine
108. The data content provider engine 108 may transmit the redirect
data instruction to the data redirection engine 128 for redirection
to alternative data consistent with a workplace established
setting. The data redirection engine 128 may transmit the
redirection to the data content provider engine 108. Data content
provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a workplace established
setting may include displaying a different webpage including only
information consistent with a workplace established setting such as
"do not display links to social networking websites."
[0976] Operation 1904 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a user history
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a user history setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a user history setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. For instance, displayed alternative data may be
consistent with a user history such as having viewed only music
related data and pages.
[0977] FIG. 154 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 2002, an operation 2004, and/or an operation 2006.
[0978] Operation 2002 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of redirecting to alternative
data consistent with a safety setting (e.g. another website). For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the redirect to alternative data consistent with a safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a safety setting may include displaying a different
webpage including only information consistent with a safety setting
such as "do not display links requesting credit card
information."
[0979] Operation 2004 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a workplace safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a workplace safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a workplace safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace safety setting. The
data redirection engine 128 may transmit the redirection to the
data content provider engine 108. Data content provider engine 108
may then display the alternative data. Displaying alternative data
consistent with a workplace safety setting may include displaying a
different webpage including only information consistent with a
workplace safety setting such as "do not display links requesting
information on this computer."
[0980] Operation 2006 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a child safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a child safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a child safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
child safety setting may include displaying a different webpage
including only information consistent with a child safety setting
such as "do not display links containing trailers for rated `R`
movies."
[0981] FIG. 155 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 240 may include at least one
additional operation. Additional operations may include an
operation 2102, an operation 2104, an operation 2106, and/or an
operation 2108.
[0982] Operation 2102 illustrates displaying alternative data
consistent with a public safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
I A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a public safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a public safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a public safety setting
instruction to the data content provider engine 108. The data
content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a public safety setting. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then display the alternative data. Displaying alternative data
consistent with a public safety setting may include displaying a
different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[0983] Operation 2104 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, data provider engine 108 (FIG. 1A) may be in communication
with Effect of content acceptability determination engine 106 (FIG.
1A), which may receive data and an associated data content
determination from data content determination engine 104 (FIG. 1A)
post retrieval of data by data retriever engine 102 (FIG. 1A).
Effect of content acceptability determination engine 106 may
transfer effect of content acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a home safety
setting (e.g. another website). For instance, data content provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of content acceptability
determination engine 106 (FIG. 1A). Each of virtual machines 11, 12
and/or 13 may include one or more instruction generating modules
configured to provide a redirect instruction to the Effect of
content acceptability determination engine 106 after a comparison
of an activation of a link to a home safety setting stored in a
copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the redirect to
alternative data consistent with a home safety setting instruction
to the data content provider engine 108. The data content provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data content provider
engine 108. Data content provider engine 108 may then display the
alternative data. Displaying alternative data consistent with a
home safety setting may include displaying a different webpage
including only information consistent with a home safety setting
such as "do not display links requesting address information."
[0984] Operation 2106 illustrates automatically redirecting to
alternative data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of content
acceptability determination engine 106 (FIG. 1A), which may receive
data and an associated data content determination from data content
determination engine 104 (FIG. 1A) post retrieval of data by data
retriever engine 102 (FIG. 1A). Effect of content acceptability
determination engine 106 may transfer effect of content
acceptability determination to the data provider engine 108 to
provide the data display option of redirecting to alternative data
(e.g. another website) consistent with a user preference. For
instance, data content provider engine 108 may receive at least one
redirect instruction from at least one component of Effect of
content acceptability determination engine 106 (FIG. 1A). Each of
virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of content acceptability determination
engine 106 after a comparison of an activation of a link to a user
preference stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect
of content acceptability determination engine 106 may communicate
the redirect to alternative data consistent with the user
preference instruction to the data content provider engine 108. The
data content provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with the user preference. The data
redirection engine 128 may transmit the redirection to the data
content provider engine 108. Data content provider engine 108 may
then automatically (e.g. prior to alerting a user) display the
alternative data. For instance, a real machine 130 may be
automatically redirected to an acceptable web link, or a page of
acceptable data.
[0985] Further, operation 2108 illustrates providing a list of
selectable alternative data options. Continuing the example above,
data provider engine 108 (FIG. 1A) may be in communication with
Effect of content acceptability determination engine 106 (FIG. 1A),
which may receive data and an associated data content determination
from data content determination engine 104 (FIG. 1A) post retrieval
of data by data retriever engine 102 (FIG. 1A). Effect of content
acceptability determination engine 106 may transfer effect of
content acceptability determination to the data provider engine 108
to provide the data display option of providing a list of
selectable alternative data options (e.g. a list of alternative
websites) consistent with a user preference. For instance, data
content provider engine 108 may receive at least one provide
selectable alternatives instruction from at least one component of
Effect of content acceptability determination engine 106 (FIG. 1A).
Each of virtual machines 11, 12 and/or 13 may include one or more
instruction generating modules configured to transmit a provide
selectable alternatives instruction to the Effect of content
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12 and/or 13. Effect of content acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data content provider engine 108.
The data content provider engine 108 may transmit the provide
selectable alternatives instruction to the data redirection engine
128 to provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data content provider engine 108.
Data content provider engine 108 may then display the list of
selectable alternatives. For instance, the list of selectable
alternative data options may include a list of acceptable web links
or a selectable list of web pages. Selectable web links and web
pages may include a thumbnail image of the first page of the web
link or of the web page.
[0986] FIG. 156 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 230 may include at least one
additional operation. Additional operations may include an
operation 2202, an operation 2204, an operation 2206, and/or an
operation 2208.
[0987] At the operation 2202, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the content of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 encompassing
a virtual machine representation of real machine 130, post (e.g.
subsequent to) activation of Link 1, Link 2, and Link 3,
respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. 1B further illustrates virtual machines 11,
12 and/or 13 including a virtual machine representation of content
of the real machine 130 post activation of Link 1, Link 2, and/or
Link 3, respectively. Examples of such content include a movie,
music file, a script (e.g., Java script or Active X control), a
markup language, an email, etc. downloaded onto real machine 130
from one or more sources associated with activation/traversal of
Link 1, Link 2, and/or Link 3. An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation may include determining
an acceptability of an effect of the content of the data at least
in part via a virtual machine representation of at least a portion
of the content of the real machine include determining whether or
not a video or image has been loaded onto, for example, the virtual
machine 11 after loading at least a portion of the data contained
in Link 1.
[0988] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the content of the real machine on a
virtual machine representation of at least a portion of a real
machine generated by, for example, virtual machine 11. FIG. 1C
illustrates a partial follow-on operational view of real machine
130 (e.g., a desktop, notebook, or other type computing system) in
which at least a portion of system 100 (FIG. 1A) has been
implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0989] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6 post traversal of
Link 1. Accordingly, FIG. 1C illustrates system 100 generating
virtual machine representations of real machine 130, used to
traverse Links 4, 5, and 6, in the context of virtual machines 21,
22, and 23, respectively. Those skilled in the art will thus
appreciate that, in the example shown in FIG. 1C, system 100 is
creating second-order virtual machine representations to
prospectively investigate the effects on the states of various
components of real machine 130 via sequential traversals of links.
That is, the virtual machine representations of real machine 130
encompassed in virtual machine 21, virtual machine 22, and virtual
machine 23 of FIG. 1C are generated by system 100 based on the
first-order virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0990] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of content
(e.g., a movie, web page, music file, etc.) of the real machine 130
post sequential activation of Link 1 then Link 4, virtual machine
22 including a virtual machine representation of content (e.g. a
graphical image, a text file, an email, etc) of the real machine
130 post (e.g., subsequent to) sequential activation of Link 1 then
Link 5, and virtual machine 23 encompassing a virtual machine
representation of the content (e.g. a music file) of the real
machine 130 post sequential activation of Link 1 then Link 6. A
determination of an acceptability of an effect of the content of
data on the content of the real machine made on virtual machine 21
may include determining whether or not an audio file has been
loaded onto virtual machine 21. Virtual machine 21 may communicate
a determination of an acceptability of an effect of the content of
data determination made on a virtual machine 21 which may be at
least a portion of content of the real machine to virtual machine
11, which may communicate the acceptability of an effect of the
content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0991] At the operation 2204, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 encompassing
a virtual machine representation of real machine 130, post (e.g.
subsequent to) activation of Link 1, Link 2, and Link 3,
respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. 1B illustrates virtual machine 11 including
a virtual machine representation of software (e.g., a state of
software) of the real machine 130 post (e.g. subsequent to)
activation of Link 1. Examples of such software might include a
commercial word processing program or suite of programs (e.g.
Microsoft.RTM. Office for Windows), an open source Web browser
(e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up (e.g., an
executing JavaScript.TM. and/or data retrieved by same via an
XML-like scheme), or a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware programs (e.g., such as those of Symantec
Corporation or McAfee, Inc.), etc. An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation may include determining
an acceptability of an effect of the content of the data at least
in part via a virtual machine representation of at least a portion
of the software of the real machine include determining whether or
not an unauthorized program or suite of programs (e.g. music
downloading software) has been loaded, for example, onto virtual
machine 12 after loading at least a portion of the data contained
in Link 2.
[0992] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the software of the real machine on a
virtual machine representation of at least a portion of the
software of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0993] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0994] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
software (e.g.) of the real machine 130 post sequential activation
of Link 1 then Link 4, virtual machine 22 including a virtual
machine representation of software (e.g. an AJAX mashup) of the
real machine 130 post sequential activation of Link 1 then Link 5,
and a virtual machine representation of the software (e.g. a
commercial database management system) of the real machine 130 post
sequential activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the software
of the real machine made on virtual machine 21 may include
determining whether or not malware or grayware has been loaded onto
virtual machine 21. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
software of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0995] At the operation 2206, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the hardware of the
real machine. Continuing the example above, FIG. 1A illustrates the
Effect of content acceptability determination engine 106. Effect of
content acceptability determination engine 106 may receive a data
content determination from data content determination engine 104
post retrieval of data by data retriever engine 102. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
includes virtual machines 11, 12 and/or 13. Effect of content
acceptability determination engine 106 may transfer data received
from data content determination engine 104 following a
determination of data content. Effect of content acceptability
determination engine 106 may transfer the data and associated data
content determination to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13 and transfer the data and associated data content
determination to at least one of virtual machines 11, 12 and/or 13.
FIG. 1B illustrates virtual machines 11, 12 and/or 13 encompassing
a virtual machine representation of real machine 130, post (e.g.
subsequent to) activation of Link 1, Link 2, and Link 3,
respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2 or link 3 actually been traversed on real
machine 130). FIG. 1B illustrates virtual machine 11 including a
virtual machine representation of hardware (e.g. a state of the
hardware) of the real machine 130 post activation of Link 1.
Examples of such hardware might include all or part of a chipset
(e.g., data processor and/or graphics processor chipsets such as
those of Intel Corporation and/or NvidiaCorporation), a memory chip
(e.g., flash memory and/or random access memories such as those of
Sandisk Corporation and/or Samsung Electronics, Co., LTD), a data
bus, a hard disk (e.g., such as those of Seagate Technology, LLC),
a network adapter (e.g., wireless and/or wired LAN adapters such as
those of Linksys and/or CiscoTechnology, Inc.), printer, a
removable drive (e.g., flash drive), a cell phone, etc. An example
of determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a portion of the hardware of the real machine include
determining whether a network adapter on, for example, virtual
machine 12 has been disabled after loading at least a portion of
the data contained in Link 2.
[0996] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine may also
include determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the hardware of the real machine on a
virtual machine representation of at least a portion of the
hardware of a real machine generated by, for example, virtual
machine 11. FIG. 1C illustrates a partial follow-on operational
view of real machine 130 (e.g., a desktop, notebook, or other type
computing system) in which at least a portion of system 100 (FIG.
1A) has been implemented (e.g., a follow-on operational view of the
systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1C
illustrates a drill-down view of an example of the virtual machine
11 including a virtual machine representation of the content of the
real machine 130 post activation of Link 1 (e.g., a drill-down on
the systems/methods shown/described in relation to FIG. 1B). In
this drill down example, depicted is the virtual machine
representation of the content of the real machine 130 post
activation of Link 1.
[0997] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of virtual machine 11 as
shown/described in relation to FIG. 1B.
[0998] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
hardware (e.g. the circuitry or processor of the real machine) of
the real machine 130 post sequential activation of Link 1 then Link
4, a virtual machine representation of hardware (e.g. a network
adapter) of the real machine 130 post sequential activation of Link
1 then Link 5, and a virtual machine representation of the hardware
(e.g. a removable drive) of the real machine 130 post sequential
activation of Link 1 then Link 6. A determination of an
acceptability of an effect of the content of data on the hardware
of the real machine made on virtual machine 21 may include
determining whether a decrease in processor speed of virtual
machine 21 has occurred. Virtual machine 21 may communicate a
determination of acceptability of an effect of the content of data
on a virtual machine representation of at least a portion of
hardware of the real machine made on virtual machine 21 to virtual
machine 11, which may communicate the acceptability of an effect of
the content of data determination to the virtual machine module 118
(FIG. 1A) for communication to the Effect of content acceptability
determination engine 106 (FIG. 1A).
[0999] At the operation 2208, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the operating
system of the real machine. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102. FIG. 1A further illustrates the Effect of content
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Virtual
machine module 118 includes virtual machines 11, 12 and/or 13.
Effect of content acceptability determination engine 106 may
transfer data received from data content determination engine 104
following a determination of data content. Effect of content
acceptability determination engine 106 may transfer the data and
associated data content determination to the virtual machine module
118. Virtual machine module 118 (FIG. 1A) may spawn at least one
virtual machine 11, 12, and/or 13 and transfer the data and
associated data content determination to at least one of virtual
machines 11, 12 and/or 13. FIG. 1B illustrates virtual machines 11,
12 and/or 13 encompassing a virtual machine representation of real
machine 130, post (e.g. subsequent to) activation of Link 1, Link
2, and Link 3, respectively (e.g., as at least a part of real
machine 130 would exist had link 1, link 2, and/or link 3 actually
been traversed on real machine 130). FIG. 1B also illustrates
virtual machine 11 including a virtual machine representation of an
operating system (e.g., a state of an operating system and/or
network operating system) of the real machine 130 post activation
of Link 1. Examples of such an operating system might include a
computer operating system (e.g., e.g. Microsoft.RTM. Windows 2000,
Unix, Linux, etc) and/or a network operating system (e.g., the
Internet Operating System available from Cisco Technology, Inc.
Netware.RTM. available from Novell, Inc., and/or Solaris available
from Sun Microsystems, Inc.). An example of determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a portion of
an operating system of the real machine include determining whether
a portion of the operating system (e.g. Microsoft Vista) on for
example, virtual machine 12 has been disabled after loading at
least a portion of the data contained in Link 2.
[1000] Determining an acceptability of an effect of the content of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the content
of the data at least in part via a virtual machine representation
of at least a portion of the operating system of the real machine
may also include determining an acceptability of an effect of the
content of the data at least in part via a virtual machine
representation includes determining an acceptability of an effect
of the content of the data at least in part via a virtual machine
representation of at least a portion of the operating system of the
real machine on a virtual machine representation of at least a
portion of the operating system of a real machine generated by, for
example, virtual machine 11. FIG. 1C illustrates a partial
follow-on operational view of real machine 130 (e.g., a desktop,
notebook, or other type computing system) in which at least a
portion of system 100 (FIG. 1A) has been implemented (e.g., a
follow-on operational view of the systems/methods illustrated as in
FIG. 1B). Specifically, FIG. 1C illustrates a drill-down view of an
example of the virtual machine 11 including a virtual machine
representation of the content of the real machine 130 post
activation of Link 1 (e.g., a drill-down on the systems/methods
shown/described in relation to FIG. 1B). In this drill down
example, depicted is the virtual machine representation of the
content of the real machine 130 post activation of Link 1.
[1001] In some instances, system 100 may use additional virtual
machine representations of at least a part of real machine 130 to
prospectively traverse Link 4, Link 5, and Link 6. Accordingly,
FIG. 1C illustrates system 100 generating virtual machine
representations of real machine 130, used to traverse Links 4, 5,
and 6, in the context of virtual machines 21, 22, and 23,
respectively. Those skilled in the art will thus appreciate that,
in the example shown in FIG. 1C, system 100 is creating
second-order virtual machine representations to prospectively
investigate the effects on the states of various components of real
machine 130 via sequential traversals of links. That is, the
virtual machine representations of real machine 130 encompassed in
virtual machine 21, virtual machine 22, and virtual machine 23 of
FIG. 1C are generated by system 100 based on the first-order
virtual machine representation of a virtual machine as
shown/described in relation to FIG. 1B.
[1002] FIG. 1C illustrates virtual machine 21 encompassing a
virtual machine representation of real machine 130 post (e.g.
subsequent to) a sequential activation of Link 1 (e.g., as shown on
FIG. 1B) then Link 4 (e.g., as shown on FIG. 1C). FIG. 1C
illustrates that in one instance virtual machine 21 may be run on
core 31 of a multi-core processor. FIG. 1C illustrates system 100
traversing Links 4, 5, and/or 6 via a virtual machine
representation of real machine 130 encompassed within virtual
machines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtual
machine 21 including a virtual machine representation of the
operating system (e.g. Linux) of the real machine 130 post
sequential activation of Link 1 then Link 4, a virtual machine
representation of an operating system (e.g. Mac OS/X) of the real
machine 130 post sequential activation of Link 1 then Link 5, and a
virtual machine representation of the operating system (e.g. GNU,
Berkeley Software Distribution) of the real machine 130 post
sequential activation of Link 1 then Link 6 (e.g., as such might
appear after activation of a link installed by a rootkit via
malware/spyware). A determination of an acceptability of an effect
of the content of data on the operating system of the real machine
made on virtual machine 21 may include determining whether or not a
rootkit has been installed onto virtual machine 21. Virtual machine
21 may communicate a determination of acceptability of an effect of
the content of data on a virtual machine representation of at least
a portion of operating system of the real machine made on virtual
machine 21 to virtual machine 11, which may communicate the
acceptability of an effect of the content of data determination to
the virtual machine module 118 (FIG. 1A) for communication to the
Effect of content acceptability determination engine 106 (FIG.
1A).
[1003] FIG. 157 illustrates alternative embodiments of the example
operational flow 200E of FIG. 136 where the providing at least one
data display option operation 230 may include at least one
additional operation. Additional operations may include an
operation 2302, an operation 2304, and/or an operation 2306.
[1004] At the operation 2302, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least a part of a computing device. FIG.
1D illustrates real machine 130 including at least a part of a
computing device 132. The computing device 132 may be any device
capable of processing one or more programming instructions. For
example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[1005] At the operation 2304, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device. Continuing
the example above, FIG. 1A illustrates the Effect of content
acceptability determination engine 106. Effect of content
acceptability determination engine 106 may receive a data content
determination from data content determination engine 104 post
retrieval of data by data retriever engine 102 and communication of
retrieved data to data content determination engine 104. FIG. 1A
further illustrates the Effect of content acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
may spawn virtual machines 11, 12 and/or 13 that may be virtual
machine representations of at least a part of real machine 130.
Real machine 130 may include at least one peripheral device. For
instance, FIG. 1D illustrates real machine 130 including at least
one peripheral device 134-146. FIG. 1D illustrates a representative
view of an implementation of real machine 130 (e.g., a desktop,
notebook, or other type computing system, and/or one or more
peripheral devices) in which all/part of system 100 may be
implemented. FIG. 1D illustrates that implementations of real
machine 130 may include all/part of computing device 132 and/or
all/part of one or one or more peripherals associated computing
device 132.
[1006] At the operation 2306, the determining an acceptability of
an effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine having
one or more end-user specified preferences includes determining an
acceptability of an effect of the content of the data at least in
part via a virtual machine representation of at least a part of a
real machine including at least one peripheral device includes
determining an acceptability of an effect of the content of the
data at least in part via a virtual machine representation of at
least a part of a real machine having one or more end-user
specified preferences includes determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a part of a real machine
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, FIG. 1A
illustrates the Effect of content acceptability determination
engine 106. Effect of content acceptability determination engine
106 may receive a data content determination from data content
determination engine 104 post retrieval of data by data retriever
engine 102 and communication of retrieved data to data content
determination engine 104. FIG. 1A further illustrates the Effect of
content acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 may spawn virtual machines 11, 12 and/or
13 that may be virtual machine representations of at least a part
of real machine 130. Real machine 130 may include at least one
peripheral device. For instance, FIG. 1D illustrates a real machine
may also include at least a portion of one or more peripheral
devices connected/connectable (e.g., via wired, waveguide, or
wireless connections) to real machine 130. Peripheral devices may
include one or more printers 134, one or more fax machines 136, one
or more peripheral memory devices 138 (e.g., flash drive, memory
stick), one or more network adapters 139 (e.g., wired or wireless
network adapters), one or more music players 140, one or more
cellular telephones 142, one or more data acquisition devices 144
(e.g. robots) and/or one or more device actuators 146 (e.g., an
hydraulic arm, a radiation emitter, or any other component(s) of
industrial/medical systems).
Application Ser. No. 12/154,148 (1206-003-007C1-000000)
[1007] FIG. 158 illustrates an operational flow 200F After a start
operation, the operational flow 200F moves to an operation 210.
Operation 210 illustrates retrieving at least a portion of data
from a data source (e.g. a computer accessible from the internet).
For example, FIG. 1A illustrates a data retriever engine 102. Data
retriever engine 102 may retrieve (e.g. download) data 110 (e.g. a
web page) from a data source such as a computer accessible from the
internet. For example, data retriever engine 102 may set a URL and
add a query string value to the URL. Data retriever engine 102 may
then make a request to the URL and scan the response received from
the URL. Data 110 may be a web site or web page containing one or
more links to additional web sites, such as shown, for example, in
FIG. 1B and/or FIG. 1C. Data 110 may in some instances be textual,
a two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content.
[1008] Then, operation 220 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates an Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. Effect of data
acceptability determination engine 106 (FIG. 1A) may utilize, for
example, virtual machine 12 (FIG. 1A) spawned by virtual machine
module 118 to determine whether data associated with Link 2 would
result in a change in the operating system of real machine 130
contra to a user preference regarding the operating system as
stored in the user preference database 120.
[1009] Then, operation 230 illustrates providing at least one data
display option to the end user's real machine based on the
determining acceptability of the effect of the retrieved at least a
portion of the data. FIG. 1A illustrates a data provider engine
108. Data provider engine 108 may be in communication with Effect
of data acceptability determination engine 106, which may receive
data from data retriever engine 102. Effect of data acceptability
determination engine 106 may transfer at least an effect of data
acceptability determination to the data provider engine 108 to
provide at least one data display option. In one example, data
provider engine 108 (FIG. 1A) provides data via placing the data on
a visual display, where the data is such that it meets one or more
thresholds associated with the effect of data acceptability
determination. Provided data may be a list of web links, a web
page, or other data (e.g., text, video, audio) that either have
been deemed acceptable by Effect of data acceptability
determination engine 106 or that have been modified (e.g.,
obfuscated), such as by data modification engine 122, such that the
to-be-displayed data is determined to be acceptable under user
preferences. Display option may include providing a visual display
of the data (e.g., displaying text, playing a video, etc.),
providing an audible presentation of the data (e.g., playing an
audio file), providing a mixed media display of the data (e.g.,
playing a video and an associated audio file), and so on. Provided
data may be modified via the data modification engine 122. For
instance, provided data may be obfuscated via the data obfuscation
engine 124 (e.g., at least a portion of the displayed data may be
blurred out or disabled), or provided data may be anonymized via
the data anonymization engine 126 (e.g., at least a portion of the
data may be deleted entirely). Data provider engine 108 (FIG. IA)
may receive at least one display instruction (e.g. OK to display
links 1 and 2) from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, each of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machines 11, 12, and/or 13. Such instruction may
include an instruction to the data provider engine 108 to prevent
the data provider engine 108 from displaying data that may
configure a hardware profile of real machine 130 counter to
anti-viral settings stored in the user preference database 120
(FIG. 1A), or an instruction to the data provider engine 108 to
prevent the data provider engine 108 from displaying data that may
configure an operating system of real machine 130 counter to a
previous operating system of the real machine (130) (e.g. determine
if a rootkit has been installed).
[1010] FIG. 159 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[1011] The operation 302 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining a database of known data for
data information. Continuing the example above, data retriever
engine 102 (FIG. 1A) may retrieve data 110 retrieved from a data
source by the data retriever engine 102 and communicate data 110 to
Effect of data acceptability engine 106, which transfers data 110
to the database examination engine 112. Database examination engine
112 may be configured to examine a database of data provided, for
example, by a data provider service or a database of data stored on
a real machine 130 and compare examined database data to the
retrieved data 110. Effect of data acceptability determination
engine 106 may utilize format/protocol information to determine
whether database examination engine should call a specific database
or library (e.g., a Windows Media Player library) to obtain file
information. File information may be utilized to compare retrieved
data 110 to data stored in a library. For instance, a database may
include a list of links viewed by a user or pre-approved by a user
based on one or more user-specified preferences, such as links from
a specific source of information (e.g., the Roman Catholic Church)
and may provide an indication to the Effect of data acceptability
engine 106 that data 110 is pre-approved data.
[1012] The operation 304 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by traversing data in real time. Continuing
the example above, data retriever engine 102 (FIG. 1A) may
retrieve
[1013] data 110 retrieved from a data source by the data retriever
engine 102 and communicate data 110 to Effect of data acceptability
engine 106, which transfers data 110 to the data transverser engine
114. Data transverser engine 114 may traverse links of data 110.
For instance, data transverser engine 114 may be configured to
traverse (e.g., scan) the data 110 to determine the content of the
data (e.g., text, images, video files). Accordingly, FIG. 1B
illustrates virtual machine 11 encompassing a virtual machine
representation of real machine 130, post activation of Link 3
(e.g., representative of one or more states of one or more
hardware/software/firmware components of/resident within real
machine 130). Data traversal may occur in real time (e.g.,
simultaneously as data is loading). Upon traversal of at least a
portion of Link 3 by the data transverser engine 114, Effect of
data acceptability determination engine 106 may determine whether
an effect of the retrieved data is acceptable to a user based on a
user's preferences by comparing the traversed data to one or more
user preferences stored in a user preference database 120 (FIG.
1A).
[1014] The operation 306 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by locally examining data. For instance,
continuing the example above, Effect of data acceptability engine
106 may receive data 110 retrieved from a data source (e.g. a
computer accessible through the internet) by the data retriever
engine 102 and communicate data 110 to a local data examination
engine 116 (FIG. 1A) of virtual machine 11. Local data examination
engine 116 may extract data content information from at least a
portion of the data. Local data examination engine 116 may locally
(e.g., on the real machine 130) examine (e.g., analyze) at least a
portion of the data (e.g., one or more pointers in the data) to
determine data content (e.g., an audio file is a .wav file). For
instance, local data examination engine 116 may view an amount of
html source code to locate markers signifying the format of at
least a portion of data content. The local examination engine 116
may examine the data 110 on the real machine 130 at the location of
the real machine 130 (e.g. executed on a subsystem within an end
user's real machine) to determine data content (e.g. a downloadable
software program).
[1015] FIG. 160 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, and/or an operation
406.
[1016] The operation 402 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining data to locate references to
additional data. Continuing the example above, FIG. 1A illustrates
the Effect of data acceptability determination engine 106. Effect
of data acceptability determination engine 106 may receive data
from data retriever engine 102. FIG. 1A further illustrates the
Effect of data acceptability determination engine 146 further
including a virtual machine module 118 and a user preference
database 120. Effect of data acceptability determination engine 106
may transfer the data to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13, and transfer the data to at least one of virtual
machines 11, 12, and/or 13 further including data transverser
engine 114 and local data examination engine 116. At least one of
virtual machines 11, 12, and/or 13 may utilize at least one of data
transverser engine 114 and local data examination engine 116 to
examine (e.g. scan) at least a portion of data (e.g. an imbedded
link on a webpage) to determine if the data references additional
data (e.g. one or more additional links). Additional data may be a
web page comprising text and/or an image, a link to a web page, a
video or any combination of text, images, links to web pages, or
videos. Virtual machines 11, 12, and/or 13 may traverse additional
data to determine an acceptability of an effect of the data. Effect
of data acceptability determination may be communicated to Effect
of data acceptability determination engine 106 that may communicate
an effect of data acceptability determination to a data provider
engine 108.
[1017] The operation 404 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by determining whether data references
additional data when loading. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer retrieved data to the virtual machine
module 118. Virtual machine module 118 (FIG. 1A) may spawn at least
one virtual machine 11, 12, and/or 13, and transfer the data to at
least one of virtual machines 11, 12, and/or 13 further including
data transverser engine 114 and local data examination engine 116.
At least one of virtual machines 11, 12, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine retrieved data in real time as it loads. For
instance, if a link to a webpage immediately (e.g. as soon as the
link is activated) references an additional link (e.g. to redirect
a user), a virtual machine 11, 12, and/or 13 may determine that
such a reference to an additional link (e.g., a pop-up, selectable
URL) has been made. Virtual machines 11, 12, and/or 13 may
determine whether data references additional data at any time when
the data is loading. Effect of data acceptability determination
engine 106 may communicate an effect of data acceptability
determination to a data provider engine 108.
[1018] The operation 406 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by issuing a request to a remote computer for
additional data information. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer retrieved data to the virtual machine
module 118. Virtual machine module 118 (FIG. 1A) may spawn at least
one virtual machine 11, 12, and/or 13 and transfer the data to at
least one of virtual machines 11, 12, and/or 13 further including
data transverser engine 114 and local data examination engine 116.
At least one of virtual machines 11, 12, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine data of an additional link or links and issue
a request to receive additional data information from the remote
computer or remote system (e.g. a computer at a geographically
distinct location). System 100 may include any number of
communication modules (not shown) configured to communicate over
local or remote communication channels to the remote server or
remote system.
[1019] FIG. 161 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 502, an operation 504, and/or an operation
506.
[1020] The operation 502 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining a copy of data from a location
geographically distinct from a location of the retrieved at least a
portion of the data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer retrieved data
to the virtual machine module 118. FIG. 1A illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data to at least one of
virtual machines 11, 12, and/or 13 to issue a request to a remote
computer to examine additional data information at the remote
location (e.g. a remote server farm). System 100 may include any
number of communication modules (not shown) configured to
communicate over local or remote communication channels to the
remote server or remote system.
[1021] The operation 504 illustrates generating a substantial
duplicate of at least a part of an end user's real machine at a
location geographically distinct from a location of the retrieved
at least a portion of the data. Continuing the example above, a
virtual machine 11, 12, and/or 13 of the real machine 130 may be
located at a geographically distinct location such as a remote
server, or a remote system configured duplicate data from the real
machine 130 and to receive and examine real machine information
transferred to the remote server or remote system. In one
embodiment, generating a substantial duplicate of at least a part
of an end user's real machine at a location geographically distinct
from a location of the retrieved at least a portion of the data may
include a remote server or remote system gathering parameters of an
end user's real machine to assist in generating a virtual duplicate
of the end user's real machine at the remote server or remote
system (e.g. hosted on, running on, or being implemented on the
remote server or remote system).
[1022] FIG. 162 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 602, an operation 604, and/or an operation
606.
[1023] The operation 602 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of a substantial
portion of an end user's real machine having one or more end-user
specified preferences. Continuing the example above, FIG. 1B
illustrates virtual machines 11, 12, and 13 including a virtual
machine representation of content of the real machine 130, software
of the real machine 130, hardware of the real machine 130, and an
operating system of the real machine 130. Virtual machines 11, 12,
and/or 13 may include most or all of at least one of the content of
the real machine 130 (e.g. a substantial portion of the text,
image, audio, and video files of the real machine), software of the
real machine 130 (e.g. a substantial portion of any program or
suite of programs installed on the real machine), hardware of the
real machine 130 (a substantial portion of the circuitry comprising
the real machine), and/or an operating system of the real machine
130 (e.g. a substantial portion of a Windows.RTM. operating system
installed on the real machine).
[1024] The operation 604 illustrates determining an acceptability
of an effect of data at least in part via a virtual machine
representation operating at a location of the retrieved at least a
portion of the data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer retrieved data
to the virtual machine module 118. FIG. 1A illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, and/or
13. FIG. 1A further illustrates the Effect of data acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
(FIG. 1A) may spawn at least one virtual machine 11, 12, and/or 13
and transfer the data to at least one of virtual machines 11, 12,
and/or 13. In one implementation, all or part of virtual machines
11, 12, and/or 13 may be generated on the real machine 130 (e.g. as
a subsystem of real machine 130). For instance, all or part of
virtual machines 11, 12, and/or 13 may be generated on a disk, a
memory chip, a core of a multi-core processor, etc. of an end
user's real machine.
[1025] FIG. 163 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 702, an operation 704, an operation 706,
and/or an operation 708.
[1026] The operation 702 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least two virtual machines 11, 12,
and/or 13, and transfer the data to at least one of virtual
machines 11, 12, and/or 13. FIG. 1B illustrates virtual machines
11, 12, and 13 encompassing a virtual machine representation of
real machine 130, post (e.g., subsequent to) activation of Link 1,
Link 2, and Link 3, respectively (e.g., as at least a part of real
machine 130 would exist had Link 1, Link 2, and/or Link 3 actually
been traversed on real machine 130). FIG. 1B further illustrates
virtual machines 11, 12, and/or 13 including a virtual machine
representation of content of the real machine 130 post activation
of Link 1, Link 2, and/or Link 3, respectively. Examples of such
content include a movie, music file, a script (e.g., Java script or
Active X control), a markup language, an email, etc. downloaded
onto real machine 130 from one or more sources associated with
activation/traversal of Link 1, Link 2, and/or Link 3. An example
of determining an acceptability of an effect of the data at least
in part via at least two virtual machine representations of at
least a part of an end user's real machine may include determining
an acceptability of an effect of the data at least in part via a
virtual machine representation of at least a portion of the content
of the real machine and a virtual machine representation of at
least a portion of hardware of the real machine, for example, the
state of virtual machine 11 and the state of virtual machine 12
after loading at least a portion of the data contained in Link
1.
[1027] The operation 704 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate core of a system comprising
at least two cores. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. As illustrated in FIGS. 1B and
1C, each of virtual machine 11, virtual machine 12, virtual machine
13, virtual machine 21, virtual machine 22, and virtual machine 23
may operate on an individual core 11, 12, 13, 31, 32, 33,
respectively, of a multi-core processor, or virtual machine 11 may
run on one core and virtual machines 12, 13 may run on the other
core of a dual core processor such as an Intel.RTM. dual core
processor and so on. The multi-core processor may include a
plurality of processor cores packaged in one processor package. The
term core as used herein may refer, for example, to a single
processor of a multiprocessor system, or to a processor core of a
multi-core processor. Multi-core processor may be utilized as
portable computers such as laptop computers, personal digital
assistants, or desktop computers, or servers, or another form of
processor based system. Combinations of these types of platforms
may be present. The multi-core system may include a multi-core
processor, each core comprising a separate address space, and
having internal to that address space.
[1028] The operation 706 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least two of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
may operate on a separate operating system at a location of the
data (e.g. executed on a subsystem, such as the virtual machine
module 118 (FIG. A) including a plurality of virtual machines 11,
12, and/or 13 (FIG. 1B) within the real machine 130).
[1029] The operation 708 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location of the retrieved at least a portion of the data.
Continuing the example above, FIG. 1A illustrates the Effect of
data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. FIG. 1B further illustrates virtual machines 11, 12,
13. In one implementation, any of virtual machines 11, 12, 13 may
be generated on the real machine 130 (e.g. as a subsystem of real
machine 130).
[1030] The operation 710 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location geographically distinct from a location of the retrieved
at least a portion of the data. Continuing the example above, FIG.
1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. At least one virtual machine,
for example virtual machine 12, may be virtual machines operating
at geographically distinct location such as a remote server, or a
remote system configured to receive and examine real machine
information transferred to the remote system and duplicate data
from the real machine 130. In some instances, each virtual machine
may be generated on one or more separate cores of a multi-core
processor. In another embodiment, determining an acceptability of
an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location geographically distinct from a location of the retrieved
at least a portion of the data may include gathering parameters of
an end user's real machine to assist in generating a virtual
duplicate of the end user's real machine at a remote location such
as a remote server or remote computing system (e.g. hosted on,
running on, or being implemented on the remote server or remote
system).
[1031] FIG. 164 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 802, an operation 804, and/or an operation
806.
[1032] The operation 802 illustrates determining a state change of
a virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. A state change (e.g., a
decrease in memory) of at least one of virtual machines 11, 12,
and/or 13 (FIG. 1B) may be determined by a component of at least
one of virtual machines 11, 12, and/or 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[1033] The operation 804 illustrates determining a state of a
virtual machine representation prior to loading at least a portion
of data. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may determine a state of at least one component (e.g.,
the hardware) of the virtual machine prior to activation (e.g.,
before) of a link. Virtual machine state may be representative of a
state for all or at least a portion of the components (e.g.,
content, software, hardware, operating system) of the real machine
130 represented by the virtual machine 11, 12, and/or 13. For
instance, at least one of virtual machines 11, 12, and/or 13 may be
determined to be free of viruses, an amount of virtual machine
memory may be measured, or a processing speed of at least one of
virtual machines 11, 12, and/or 13 may be determined. At least one
of virtual machines 11, 12, and/or 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[1034] The operation 806 illustrates determining a state of a
virtual machine representation after loading at least a portion of
data. Continuing the example above, FIG. 1A illustrates the Effect
of data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may determine a state of at least one component (e.g.,
the hardware) of the virtual machine subsequent to (e.g., after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by at least one of virtual machines 11, 12, and/or 13
after at least a portion of the data has loaded. For instance, at
least one of virtual machines 11, 12, and/or 13 may be determined
to contain a virus, an amount of virtual machine memory may be
measured, or a processing speed of at least one of virtual machines
11, 12, and/or 13 may be determined. At least one of virtual
machines 11, 12, and/or 13 may be examined to determine, for
example, if a virus or any other undesired software is present on
the machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[1035] FIG. 165 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 902.
[1036] The operation 902 illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. An undesirable state change may
be determined by examining the changes to at least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) and comparing the state change
of at least one of virtual machines 11, 12, and/or 13 to user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. 1A)
onto at least one of virtual machines 11, 12, and/or 13. An
undesirable state change may include any undesirable state change
including, but not limited to, a decrease in memory or processing
speed and/or the presence of a virus or other undesirable software
after at least a portion of the data has loaded. Undesirable state
changes may further include an undesirable transfer of information
located on at least one of virtual machines 11, 12, and/or 13 to an
external location, an undesirable transfer of data onto at least
one of virtual machines 11, 12, and/or 13 from an external location
after at least a portion of the data has loaded on at least one of
virtual machines 11, 12, and/or 13 that may result in an undesired
change in the state of content, software, hardware or an operating
system of the real machine 130 and/or an undesirable transfer of
data onto at least one of virtual machines 11, 12, and/or 13 where
at least a portion of the transferred data may be found
objectionable when viewed by a user 10.
[1037] FIG. 166 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1002, an operation 1004, and/or an
operation 1006.
[1038] The operation 1002 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences within an acceptable amount of user interface
time. Continuing the example above, FIG. 1A illustrates an Effect
of data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. Effect of data acceptability determination
engine 106 (FIG. 1A) may utilize, for example, virtual machine 12
(FIG. 1A) spawned by virtual machine module 118 to determine
whether data associated with Link 2 would result in a change in the
operating system of real machine 130 contra to a user preference
regarding the operating system as stored in the user preference
database 120. Effect of data acceptability determination may be
determined within an acceptable amount of user interface time (e.g.
a tolerable wait time for information retrieval). An acceptable
amount of user interface time may be within a range from an amount
of time approximating an instantaneous effect of data acceptability
determination to an amount of time approximating a maximum time a
user may be willing to wait for a result before abandoning a data
retrieval (e.g., a downloading webpage).
[1039] The operation 1004 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences in approximately one-tenth of a second.
Continuing the example above, Effect of data acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to a user
preference regarding the operating system as stored in the user
preference database 120. A user interface time of approximately
one-tenth of a second may approximate an acceptable amount elapsed
time for a user to feel that the Effect of data acceptability
determination engine 106 is reacting instantaneously.
[1040] The operation 1006 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences in less than approximately 1 second.
Continuing the example above, Effect of data acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to a user
preference regarding the operating system as stored in the user
preference database 120. A user interface time of less than
approximately one second may approximate an acceptable amount
elapsed time for a user to notice a delay in the Effect of data
acceptability determination without abandoning the information
retrieval.
[1041] FIG. 167 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1102, an operation 1104, and/or an
operation 1106.
[1042] The operation 1102 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to at least one user setting. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. An acceptability of an effect of the data may be
determined by determining if a state change to at least one of
virtual machines 11, 12, and/or 13 has occurred and comparing the
state change of at least one of virtual machines 11, 12, and/or 13
to user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Comparison may be made, for
example, by transferring user preference database information from
the user preference database 120 (FIG. 1A) to the virtual machine
module 118 (FIG. 1A) which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one end-user specified preference relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. At least one of virtual machines 11,
12, and/or 13 may determine an acceptability of an effect of the
data based on at least one user setting contained in a user
preference database at least a portion of which may be spawned onto
at least one of virtual machines 11, 12, and/or 13 via virtual
machine module 118 (e.g., does a website contain only images, text,
audio or visual data suitable for viewing by a user based on a
setting established by a user such as a political or cultural
preference setting). Further examples of user preferences include
specific religion or lifestyle preference, such as "return only
links relating to Roman Catholicism" or "return only links relating
to a vegan lifestyle" that may be stored in the real machine 130.
User-specific preference may also relate to user information safety
or computer safety, such as "do not display links requesting
information from my computer," or "do not display links that
transfer viruses onto my computer."
[1043] The operation 1104 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a personal user setting. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a personal user setting (e.g., "show only
automobile related data") contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. User preference database 120 may include at least one
personal user setting relating to at least one of content,
software, hardware and/or an operating system of a real machine
130. Personal user setting may be a setting input by a user that is
personal to the user, such as an information security level, a
content filter level, or a personal desirability setting such as
"show only non-religious data" or "show only automobile related
data."
[1044] The operation 1106 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a peer user setting. Continuing the example above, user
preference database 120 may include at least one peer user setting
relating to at least one of content, software, hardware and/or an
operating system of an end user's real machine 130. Peer user
setting may be a setting input by a user that is determined by a
peer group, such as a peer group determined information security
level such as "display only 100 percent secure websites", a peer
group determined data filter level such as "filter 100% of obscene
data", or a peer group desirability setting such as "show only
classical music related data" or "show only knitting related
data."
[1045] FIG. 168 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1202, and/or an operation 1204. The
operation 1202 illustrates determining an acceptability of an
effect of the retrieved at least a portion of the data in response
to a corporate user setting. Continuing the example above, at least
one of virtual machines 11, 12, and/or 13 (FIG. 1B) may compare the
data received from the virtual machine module 118 (FIG. 1A) to a
corporate user setting contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. User preference database 120 may include at least one
corporate user setting relating to at least one of content,
software, hardware and/or an operating system of an end user's real
machine 130. Corporate user setting may be a setting input by a
corporation that is determined to the corporation, such as a
corporate desirability setting such as "show only real-estate
related data" or "show only agricultural related data."
[1046] The operation 1204 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a work safety user setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a work safety user setting contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. User preference database 120 may
include at least one work safety user setting relating to at least
one of content, software, hardware and/or an operating system of an
end user's real machine 130. Thus, in one specific example, a
webpage or website data may be determined to be displayable if the
data satisfies a work safety user setting such as a corporate
information security level, corporate user setting, or a corporate
information content filter level corporate user setting.
[1047] FIG. 169 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1302, an operation 1304, and/or an
operation 1306.
[1048] The operation 1302 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a desirability setting. Continuing the example above,
at least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
compare the data received from the virtual machine module 118 (FIG.
1A) to a desirability setting (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a desirability setting established by a user such as a
desire to view only non-obscene material) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. User preference database 120 may
include at least one desirability setting relating to at least one
of content, software, hardware and/or an operating system of an end
user's real machine 130.
[1049] The operation 1304 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a religious desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
may compare the data received from the virtual machine module 118
to a religious desirability setting (e.g., does a website contain
only images, text, audio or visual data suitable for viewing by a
user based on a religious desirability setting established by a
user such as a desire to view only Hindu material) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. A religious desirability
setting may be include any setting regarding a major, minor, or
other religion such as Christianity, Judaism, Islam, Hinduism, and
so on.
[1050] The operation 1306 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a political desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a political desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a political desirability
setting established by a user such as a desire to view only
Democratic Party material) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A political desirability setting may include any setting
regarding a political party or affiliation (e.g., Republican,
Democratic, Libertarian, Green Party, etc.).
[1051] FIG. 170 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1402, and/or an operation 1404.
[1052] The operation 1402 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a cultural desirability setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a cultural desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a cultural desirability setting
established by a user such as a desire to view only materials
regarding early Mayan civilization) contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. A cultural desirability setting may include any
culturally related information such as a religious, ethnic,
regional, or heritage based cultural desirability setting or any
other cultural desirability setting.
[1053] The operation 1404 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a theme related desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a theme related desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a theme related
desirability setting established by a user such as a desire to view
only materials regarding collectible stamps) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A theme related desirability setting
may include any theme related information, such as information
relating to cars, fashion, electronics, sports, hobbies,
collector's items, or any theme or category that may be of interest
to a user.
[1054] FIG. 171 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1502.
[1055] The operation 1502 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to an age appropriateness desirability setting. Continuing
the example above, at least one of virtual machines 11, 12, and/or
13 (FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to an age appropriateness desirability setting
(e.g., does a website contain only images, text, audio or visual
data suitable for viewing by a user based on an age appropriateness
desirability setting established by a user such as a desire to view
only materials given a PG or lower rating as determined by the
Motion Picture of America Association film rating system) contained
in user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. An age appropriateness
desirability setting may include any age appropriate setting, such
as a rating threshold or a profanity threshold.
[1056] FIG. 172 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1602, an operation 1604, and/or an
operation 1606.
[1057] The operation 1602 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to at least one privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a privacy related setting (e.g., does a
website contain only images, text, audio or visual data suitable
for viewing by a user based on a privacy related setting
established by a user) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A privacy related setting may include any privacy
related settings (e.g., does a website contain only data that will
not request information from my computer or allow others to view
personal information saved on my computer).
[1058] The operation 1604 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a user specific privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a user specific privacy related setting
(e.g., will a website request specific information about the user
such as name, address, telephone number) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A user specific privacy related setting
may include any user specific privacy related settings (e.g., a
setting relating to a user's biographical information or financial
information).
[1059] The operation 1606 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a group privacy related setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a group privacy related setting (e.g., will a website
request information about an organization such as name, address,
telephone number) contained in user preference database information
spawned on at least one of virtual machines 11, 12, and/or 13. A
group privacy related setting may include any group privacy related
settings (e.g., a setting relating to a group's membership). Group
privacy related setting may be any setting established by a group
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting.
[1060] FIG. 173 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1702, and/or an operation 1704.
[1061] The operation 1702 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a corporate privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a corporate privacy related setting (e.g.,
will a website request information about a corporation such as data
stored on a real machine belonging to the corporation) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Corporate privacy related
setting may be determined by a corporate issued privacy manual, or
other such document or mandate set forth by officers of a
corporation.
[1062] The operation 1704 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of transmitted user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of transmitted
user information setting (e.g., do not return links that will
transmit my e-mail address, home address or telephone number to an
external location) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Acceptable type of transmitted user information setting
may be determined by a user 10 (FIG. 1B). For instance,
acceptability of the effect of the data may be determined in
response to whether or not private user information, such as credit
card numbers, bank accounts, personal identification information or
any other personal user information may be transmitted to a
location external to the real machine by selecting the link.
[1063] FIG. 174 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1802, and/or an operation 1804.
[1064] The operation 1802 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of captured user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of captured
user information setting (e.g., do not return links that will
capture my e-mail address, home address or telephone number)
contained in user preference database information spawned on at
least one of virtual machines 11, 12, and/or 13. Acceptable type of
captured user information setting may be determined by a user 10
(FIG. 1B). For instance, acceptability of the effect of the data
may be determined in response to whether or not private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information
may be captured by a machine located at a location external to the
real machine by selecting the link.
[1065] The operation 1804 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of exposed user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of exposed
user information setting (e.g., do not return links that will
expose personal financial information stored on the real machine
130) contained in user preference database information spawned on
at least one of virtual machines 11, 12, and/or 13. Acceptable
types of exposed user information settings may be determined by a
user 10 (FIG. 1B). For instance, acceptability of the effect of the
data may be determined in response to whether or not private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information
may be exposed to a machine located at a location external to the
real machine by selecting the link.
[1066] FIG. 175 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1902, an operation 1904, and/or an
operation 1906.
[1067] The operation 1902 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to visually examining a data image. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. To visually examine a data image, at least one of
virtual machines 11, 12, and/or 13 (FIG. 1B) may include an image
scanning module. In one embodiment, visually examining a data image
may include computer implemented image analysis, such as, color
analysis, pattern-matching, pattern-recognition, or any other
technique for recognizing a particular image or type of image.
[1068] The operation 1904 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of content of an end user's real machine having one or more
end-user specified preferences. Continuing the example above, FIG.
1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
further illustrates virtual machines 11, 12, and 13 including a
virtual machine representation of content of the real machine 130
post activation of Link 1, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
email, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the data at least in part via a virtual machine
representation may include determining an acceptability of an
effect of the data at least in part via a virtual machine
representation of at least a portion of the content of the real
machine include determining whether or not a video or image has
been loaded onto, for example, the virtual machine 11 after loading
at least a portion of the data contained in Link 1.
[1069] The operation 1906 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of software of an end user's real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software, such as a
state of Windows Media Player) of the real machine 130 post (e.g.,
subsequent to) activation of Link 1. Examples of such software
might include a commercial word processing program or suite of
programs (e.g., Microsoft.RTM. Office for Windows), an open source
Web browser (e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up
(e.g., an executing JavaScript.TM. and/or data obtained by same via
an XML-like scheme), a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware program (e.g., such as those of Symantec
Corporation or McAfee, Inc.), a multi-media program (e.g.,
QuickTime) etc. An example of determining an acceptability of an
effect of the data at least in part via a virtual machine
representation may include determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine include determining whether or not an unauthorized
program or suite of programs (e.g., music downloading software) has
been loaded, for example, onto virtual machine 12 after loading at
least a portion of the data contained in Link 2.
[1070] FIG. 176 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1902, an operation 2004, and/or an
operation 2006.
[1071] The operation 2002 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of hardware of an end user's real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machine 11 including a virtual machine representation of hardware
(e.g., a state of the hardware) of the real machine 130 post
activation of Link 1. Examples of such hardware might include all
or part of a chipset (e.g., data processor and/or graphics
processor chipsets such as those of Intel Corporation and/or
NvidiaCorporation), a memory chip (e.g., flash memory and/or random
access memories such as those of Sandisk Corporation and/or Samsung
Electronics, Co., LTD), a data bus, a hard disk (e.g., such as
those of Seagate Technology, LLC), a network adapter (e.g.,
wireless and/or wired LAN adapters such as those of Linksys and/or
CiscoTechnology, Inc.), printer, a removable drive (e.g., flash
drive), a cell phone, etc. An example of determining an
acceptability of an effect of the data at least in part via a
virtual machine representation includes determining an
acceptability of an effect of the data at least in part via a
virtual machine representation of at least a portion of the
hardware of the real machine includes determining whether a network
adapter on, for example, virtual machine 12 has been disabled after
loading at least a portion of the data contained in Link 2.
[1072] The operation 2004 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an operating system of an end user's real machine having
one or more end-user specified preferences. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. FIG. 1B illustrates virtual machines 11, 12, and 13
encompassing a virtual machine representation of real machine 130,
post (e.g., subsequent to) activation of Link 1, Link 2, and Link
3, respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. 1B illustrates virtual machine 11 including
a virtual machine representation of an operating system (e.g., a
state of an operating system and/or network operating system) of
the real machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or a network
operating system (e.g., the Internet Operating System available
from Cisco Technology, Inc. Netware.RTM. available from Novell,
Inc., and/or Solaris available from Sun Microsystems, Inc.). An
example of determining an acceptability of an effect of the data at
least in part via a virtual machine representation includes
determining an acceptability of an effect of the data at least in
part via a virtual machine representation of at least a portion of
an operating system of the real machine include determining whether
a portion of the operating system (e.g., Microsoft Vista) on for
example, virtual machine 12 has been disabled after loading at
least a portion of the data contained in Link 2.
[1073] The operation 2006 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least a portion of a computing
device. FIG. 1D illustrates real machine 130 including at least a
part of a computing device 132. The computing device 132 may be any
device capable of processing one or more programming instructions.
For example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[1074] FIG. 177 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 2102, and/or an operation 2104.
[1075] The operation 2102 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least one peripheral device.
Continuing the example above, FIG. 1A illustrates the Effect of
data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13 that may be a virtual machine representation of at least a part
of real machine 130. Real machine 130 (FIG. 1B) may include at
least one peripheral device. For instance, FIG. 1D illustrates real
machine 130 including at least one peripheral device 134-146. FIG.
1D illustrates a representative view of an implementation of real
machine 130 (e.g., a desktop, notebook, or other type computing
system, and/or one or more peripheral devices) in which a part of
system 100 may be implemented. FIG. 1D illustrates that
implementations of real machine 130 may include all/part of
computing device 132 and/or all/part of one or one or more
peripherals associated computing device 132.
[1076] The operation 2104 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least one peripheral device
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one of
virtual machines 11, 12, and/or 13 that may be a virtual machine
representation of at least a part of real machine 130. Real machine
130 may include at least one peripheral device. For instance, FIG.
1D illustrates an end user's real machine may also include at least
a portion of one or more peripheral devices connected/connectable
(e.g., via wired, waveguide, or wireless connections) to real
machine 130. Peripheral devices may include one or more printers
134, one or more fax machines 136, one or more peripheral memory
devices 138 (e.g., flash drive, memory stick), one or more network
adapters 139 (e.g., wired or wireless network adapters), one or
more music players 140, one or more cellular telephones 142, one or
more data acquisition devices 144 (e.g., robots) and/or one or more
device actuators 146 (e.g., a computer-controlled manufacturing
device, medical device, an hydraulic arm, a radiation emitter, or
any other component(s) of industrial/medical systems).
[1077] FIG. 178 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2202, and/or an operation 2204.
[1078] The operation 2202 illustrates providing a data display
option of displaying the retrieved at least a portion of the data.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying at least a portion of the data. For
instance, data provider engine 108 may receive at least one display
instruction (e.g., OK to display the entire text of link 1) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. Data provider engine 108 may then
display the data. Displayed data may be an unmodified web page of
text, images and/or video, or a web page including links to
additional web pages and may be displayed on an end user's real
machine display such as a computer screen.
[1079] The operation 2204 illustrates providing a data display
option of not displaying the retrieved at least a portion of the
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of not displaying at least a portion of the data.
For instance, data provider engine 108 may receive at least one do
not display instruction (e.g., Do not display the text of link 1)
from at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may include one or more
instruction generating modules configured to provide a do not
display instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the do not display instruction to the data provider
engine 108. The data display option of not displaying the data may
include a message indicated why the data is not being displayed, or
may be, for example, a blank page displayed on a display of the
real machine.
[1080] FIG. 179 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
May include an operation 2302, an operation 2304, and/or an
operation 2306.
[1081] The operation 2302 illustrates providing a data display
option of displaying a modified version of the retrieved at least a
portion of the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of data
acceptability determination engine 106 (FIG. 1A), which may receive
data from data obtainer engine 102 (FIG. 1A). Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a modified
version of the data. For instance, data provider engine 108 (FIG.
1A) may receive at least one modify data instruction (e.g., display
only lines 1-10 of the text of link 1) from at least one component
of Effect of data acceptability determination engine 106 (FIG. 1A).
At least one of virtual machines 11, 12, and/or 13 may include one
or more instruction generating modules configured to provide a
modify data instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the modify data instruction to the data provider
engine 108. The data provider engine 108 may transmit the modify
data instruction to the data modification engine 122 for
modification of the data. Data modification engine may transmit the
modified data to the data provider engine 108. Data provider engine
108 may then display the modified version of the data. Displayed
data may be a modified web page of text, a modified image and/or a
modified video, or a modified web page including links to
additional web pages. For instance, a webpage or website may be
displaying, but any obscenities on the web page or website may
replaced by non-obscene word alternatives.
[1082] The operation 2304 illustrates providing a data display
option of obfuscating an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of data acceptability determination
engine 106 (FIG. 1A), which may receive data from data obtainer
engine 102 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
to the data provider engine 108 to provide the data display option
of obfuscating (e.g., blurring) a portion of the data (e.g.,
obscene photos). For instance, data provider engine 108 may receive
at least one obfuscate data instruction (e.g., display only
non-obscene portions of the image in link 1) from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 (FIG.
1B) may include one or more instruction generating modules
configured to provide an obfuscate data instruction to the Effect
of data acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the obfuscate data
instruction to the data provider engine 108. The data provider
engine 108 may transmit the obfuscate data instruction to the data
modification engine 122 which may transmit the obfuscate data
instruction to the data obfuscation engine 124. Data obfuscation
engine 124 may transmit the obfuscated data to the data
modification engine 122 for transmission to the data provider
engine 108. Data provider engine 108 may then display the
obfuscated version of the data. For example, obfuscating logic may
obfuscate restricted data or imagery within a webpage or image.
Obfuscation may include blurring or blocking of the objectionable
data portion.
[1083] The operation 2306 illustrates providing a data display
option of anonymizing an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of data acceptability determination
engine 106 (FIG. 1A), which may receive data from data obtainer
engine 102 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
and an instruction to the data provider engine 108 to provide the
data display option of anonymizing (e.g., obscuring source
information) for a portion of the data (e.g., graphic videos). For
instance, data provider engine 108 may receive at least one
anonymize data instruction (e.g., obscure source information for
portions of the video in link 1) from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide an
anonymize data instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the anonymize data instruction to the data provider
engine 108. The data provider engine 108 may transmit the anonymize
data instruction to the data modification engine 122 which may
transmit the anonymize data instruction to the data anonymization
engine 126. Data anonymization engine 126 may transmit the
anonymized data to the data modification engine 122 for
transmission to the data provider engine 108. Data provider engine
108 may then display the anonymized version of the data. Anonymized
data may be data in which the original identity information of the
data is hidden, obscured, replaced, and/or otherwise modified.
[1084] FIG. 180 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2402, an operation 2404, and/or an
operation 2406.
[1085] The operation 2402 illustrates providing a data display
option of removing, altering, or replacing an objectionable data
portion. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination and an instruction to the data provider engine 108 to
provide the data display option of removing, altering or replacing
an objectionable data portion (e.g., replacing profanity with
innocuous language) for a portion of the data (e.g., explicit
lyrics). For instance, data provider engine 108 may receive at
least one alter, remove or replace instruction (e.g., obscure
source information for portions of the video in link 1) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the remove, alter or
replace data instruction to the data provider engine 108. The data
provider engine 108 may transmit the anonymize data instruction to
the data modification engine 122 which may then remove, alter or
replace the data. Data modification engine 122 may transmit the
data containing removed, altered or replaced portions to the data
provider engine 108. Data provider engine 108 may then display the
data containing removed, altered, or replaced portions. Thus, in
one specific example, a portion of a webpage produced by a search
including data relating to religions other than Catholicism may be
removed from the web page prior to display of the data on an end
user's real machine display such as a computer screen.
[1086] The operation 2404 illustrates providing a data display
option of displaying a data portion consistent with at least one
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a setting stored, for example, in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If displayed data needs to be
modified to be consistent with at least one setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 (FIG. 1A) may transmit the
modified data to the data provider engine 108. Data provider engine
108 may then display the data consistent with the setting. Thus, a
webpage or website data may be determined to be displayable if the
data satisfies a setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the setting. For instance, a
portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate setting.
[1087] The operation 2406 illustrates providing a data display
option of displaying a data portion consistent with a privacy
related setting. Continuing the example above, at least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a privacy related
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, and/or 13. Effect of
data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one
privacy related setting, the data provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data consistent with the privacy related setting. For instance, a
portion of a returned webpage including data requesting private
user information such as a user's social security number or e-mail
address may be removed from the web page prior to display of the
data on a computer screen. Further specific examples include a
webpage or website data may be determined to be displayable if the
data satisfies a setting such as a privacy related setting such as
a setting relating to a user's biographical information or
financial information, a webpage or website data may be determined
to be displayable if the data satisfies a group privacy related
setting such as a work group (e.g., employees of a company), a peer
group (e.g., members of a book club), or a family group (e.g.,
members of family unit) privacy related setting, or a webpage or
website data may be determined to be displayable if the data
satisfies a privacy setting determined by a corporation or other
organization to maintain corporate or organization privacy.
[1088] FIG. 181 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2502.
[1089] The operation 2502 illustrates providing a data display
option of displaying a data portion consistent with a user setting.
Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one user
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines (I, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one user setting, the data provider engine
108 (FIG. 1A) may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 (FIG. 1A) may transmit the modified data to
the data provider engine 108. Data provider engine 108 may then
display the data consistent with the user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a user setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the user setting. For instance,
a portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[1090] FIG. 182 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2602.
[1091] The operation 2602 illustrates providing a data display
option of displaying a data portion consistent with a desirability
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If displayed data
needs to be modified to be consistent with at least one
desirability setting, the data provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data portion consistent with the desirability setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[1092] FIG. 183 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2702.
[1093] The operation 2702 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, at least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, and/or 13. Effect of
data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one
workplace established setting, the data provider engine 108 (FIG.
1A) may transmit the modify data instruction to the data
modification engine 122 (FIG. 1A) for modification of the data.
Data modification engine 122 may transmit the modified data to the
data provider engine 108. Data provider engine 108 may then display
the data portion consistent with the workplace established setting.
For instance, the data display option may be displaying on a
display of an end user's real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[1094] FIG. 184 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2802, and/or an operation 2804.
[1095] The operation 2802 illustrates providing a data display
option of displaying a data portion consistent with a safety
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If displayed data needs to be
modified to be consistent with at least one safety setting, the
data provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data provider engine 108. Data provider
engine 108 may then display the data portion consistent with the
safety setting. For instance, the data display option may be
displaying on a display of an end user's real machine only a data
portion consistent with child safety setting such as "display only
non-violent data," or "display only ethnic and gender neutral
data."
[1096] The operation 2804 illustrates providing a data display
option of displaying a data portion consistent with a public safety
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If displayed data
needs to be modified to be consistent with at least one public
safety setting, the data provider engine 108 (FIG. 1A) may transmit
the modify data instruction to the data modification engine 122
(FIG. 1A) for modification of the data. Data provider engine 108
may then display the data portion consistent with the public safety
setting. For instance, the data display option may be displaying on
a display of an end user's real machine only a data portion
consistent with public safety setting such as "display only
non-confidential data."
[1097] FIG. 185 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2902.
[1098] The operation 2902 illustrates providing a data display
option of displaying a data portion consistent with a home safety
setting. Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one home
safety setting. For instance, data provider engine 108 may receive
at least one display instruction from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a home
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, and/or 13. Effect
of data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one home
safety setting, the data provider engine 108 (FIG. 1A) may transmit
the modify data instruction to the data modification engine 122
(FIG. 1A) for modification of the data. Data provider engine 108
may then display the data portion consistent with the home safety
setting. For instance, the data display option may be displaying on
a display of an end user's real machine only a data portion
consistent with home safety setting such as "okay to display
private or confidential data."
[1099] FIG. 186 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3002.
[1100] The operation 3002 illustrates providing a data display
option of displaying a data portion consistent with a workplace
safety setting. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data provider
engine 108 may receive at least one display instruction from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a workplace safety setting stored in a copy of the user
preference database 120 (FIG. I A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one workplace safety setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data provider engine 108 may then display
the data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
workplace safety setting such as "display only non-personal
data."
[1101] FIG. 187 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3102.
[1102] The operation 3102 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
child safety setting. For instance, data provider engine 108 may
receive at least one display instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a child safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one child safety setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data provider engine 108 may then display
the data portion consistent with the child safety setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
child safety setting such as "display only non-violent data."
[1103] FIG. 188 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3202, an operation 3204, and/or an
operation 3206.
[1104] The operation 3202 illustrates redirecting to alternative
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data retriever engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108, and an instruction
to provide the data display option of redirecting to alternative
data (e.g., another website). For instance, data provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). Each of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide a
redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect instruction to the data provider
engine 108. The data provider engine 108 may transmit the redirect
data instruction to the data redirection engine 128 for redirection
to alternative data. The data redirection engine 128 may transmit
the redirection to the data provider engine 108. Data provider
engine 108 may then display the alternative data.
[1105] The operation 3204 illustrates automatically redirecting to
alternative data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of automatically redirecting to
alternative data (e.g., another website) consistent with a user
preference. For instance, data provider engine 108 may receive at
least one automatically redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an automatically redirect instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate an automatically redirect
to alternative data consistent with the user preference instruction
to the data provider engine 108. The data provider engine 108 may
transmit the redirect instruction to the data redirection engine
128 for automatic redirection to alternative data consistent with
the user preference. The data redirection engine 128 may transmit
the automatic redirection to the data provider engine 108. Data
provider engine 108 may then automatically (e.g., prior to alerting
a user) display the alternative data. For instance, an end user's
real machine 130 may be automatically redirected to an acceptable
web link, or a page of acceptable data.
[1106] The operation 3206 illustrates providing a list of
selectable alternative data options. Continuing the example above,
Effect of data acceptability determination engine 106 may transfer
effect of data acceptability determination to the data provider
engine 108, and an instruction to provide the data display option
of providing a list of selectable alternative data options (e.g., a
list of alternative websites) consistent with a user preference.
For instance, data provider engine 108 may receive at least one
provide selectable alternatives instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
transmit a provide selectable alternatives instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data provider engine 108. The data
provider engine 108 may transmit the provide selectable
alternatives instruction to the data redirection engine 128 to
provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data provider engine 108. Data
provider engine 108 may then display the list of selectable
alternatives. For instance, the list of selectable alternative data
options may include a list of acceptable web links or a selectable
list of web pages. Selectable web links and web pages may include a
thumbnail image of the first page of the web link or of the web
page.
[1107] FIG. 189 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3302, and/or an operation 3304.
[1108] The operation 3302 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one privacy
related setting. For instance, data provider engine 108 may receive
at least one display instruction (e.g., OK to display webpage) from
at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a privacy related setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If data needs to be
modified to be consistent with at least one privacy related
setting, the data provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data provider engine 108. Data provider engine 108 may
then display the data consistent with the privacy related setting.
For instance, a portion of a returned webpage including data
requesting private user information such as a user's social
security number or e-mail address may be removed from the web page
prior to display of the data on a computer screen. Further specific
examples include a webpage or website data may be determined to be
displayable if the data satisfies a setting such as a privacy
related setting such as a setting relating to a user's biographical
information or financial information, a webpage or website data may
be determined to be displayable if the data satisfies a group
privacy related setting such as a work group (e.g., employees of a
company), a peer group (e.g., members of a book club), or a family
group (e.g., members of family unit) privacy related setting, or a
webpage or website data may be determined to be displayable if the
data satisfies a privacy setting determined by a corporation or
other organization to maintain corporate or organization
privacy.
[1109] The operation 3304 illustrates displaying alternative data
consistent with a customized user setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one customized
user setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a customized user setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one customized user setting, the data
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data consistent with the customized user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a customized user setting when at least one of virtual
machines 11, 12, and/or 13 compares the data to the customized user
setting. For instance, a portion of a webpage produced by a search
including non-English text may be removed from the web page prior
to display of the data on a computer screen. Further, in one
specific example, a webpage or website data may be determined to be
displayable if the data satisfies a customized peer user setting,
or a webpage or website data may be determined to be displayable if
the data satisfies, for instance, a customized corporate user
setting.
[1110] FIG. 190 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3402.
[1111] The operation 3402 illustrates displaying alternative data
consistent with a desirability setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one desirability
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display image) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one desirability setting, the data
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data portion consistent with the desirability setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[1112] FIG. 191 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3502, an operation 3504, and/or an
operation 3506.
[1113] The operation 3502 illustrates displaying alternative data
consistent with a workplace established setting. Continuing the
example above, data provider engine 108 may receive at least one
display instruction (e.g., do not display data) from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a workplace established setting stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one workplace established setting, the
data provider engine 108 may transmit the modify data instruction
to the data modification engine 122 for modification of the data.
Data modification engine 122 may transmit the modified data to the
data provider engine 108. Data provider engine 108 may then display
the data portion consistent with the workplace established setting.
For instance, the data display option may be displaying on a
display of an end user's real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[1114] The operation 3504 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a user
history setting (e.g., another website). For instance, data
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user history setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a user history setting
instruction to the data provider engine 108. The data provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data. For
instance, displayed alternative data may be consistent with a user
history such as having viewed only music related data and
pages.
[1115] The operation 3506 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
Effect of data acceptability determination engine 106 may transfer
effect of data acceptability determination to the data provider
engine 108, and an instruction to provide the data display option
of redirecting to alternative data consistent with a safety setting
(e.g., another website). For instance, data provider engine 108 may
receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect to alternative data consistent with a
safety setting instruction to the data provider engine 108. The
data provider engine 108 may transmit the redirect data instruction
to the data redirection engine 128 for redirection to alternative
data consistent with a safety setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a safety setting may
include displaying a different webpage including only information
consistent with a safety setting such as "do not display links
requesting credit card information."
[1116] FIG. 192 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3602, and/or an operation 3604.
[1117] The operation 3602 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a
workplace safety setting (e.g., another website). For instance,
data provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect to alternative data consistent with a
workplace safety setting instruction to the data provider engine
108. The data provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace safety setting. The
data redirection engine 128 may transmit the redirection to the
data provider engine 108. Data provider engine 108 may then display
the alternative data. Displaying alternative data consistent with a
workplace safety setting may include displaying a different webpage
including only information consistent with a workplace safety
setting such as "do not display links requesting information on
this computer."
[1118] The operation 3604 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g., another website). For instance, data provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a child safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a child safety setting instruction to the data
provider engine 108. The data provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a child safety
setting. The data redirection engine 128 may transmit the
redirection to the data provider engine 108. Data provider engine
108 may then display the alternative data. Displaying alternative
data consistent with a child safety setting may include displaying
a different webpage including only information consistent with a
child safety setting such as "do not display links containing
trailers for rated `R` movies."
[1119] FIG. 193 illustrates alternative embodiments of the example
operational flow 200F of FIG. 158 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3702, and/or an operation 3704.
[1120] The operation 3702 illustrates displaying alternative data
consistent with a public safety setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a public safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a public safety setting instruction to the data
provider engine 108. The data provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a public safety
setting. The data redirection engine 128 may transmit the
redirection to the data provider engine 108. Data provider engine
108 may then display the alternative data. Displaying alternative
data consistent with a public safety setting may include displaying
a different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[1121] The operation 3704 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a public
safety setting (e.g., another website). For instance, data provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
to the data provider engine 108, and an instruction to provide the
data display option of redirecting to alternative data consistent
with a home safety setting (e.g., another website). For instance,
data provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a home
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, and/or 13. Effect
of data acceptability determination engine 106 may communicate the
redirect to alternative data consistent with a home safety setting
instruction to the data provider engine 108. The data provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a home safety setting
may include displaying a different webpage including only
information consistent with a home safety setting such as "do not
display links requesting address information."
Application Ser. No. 12/214,784 (1206-003-007C1-000001)
[1122] FIG. 194 illustrates an operational flow 200G representing
example operations related to FIGS. 1A, 1B, 1C and 1D. After a
start operation, the operational flow 200G moves to an operation
210. Operation 210 illustrates retrieving at least a portion of
data from a data source (e.g. a computer accessible from the
internet). For example, FIG. 1A illustrates a data retriever engine
102. Data retriever engine 102 may retrieve (e.g. download) data
110 (e.g. a web page) from a data source such as a computer
accessible from the internet. For example, data retriever engine
102 may set a URL and add a query string value to the URL. Data
retriever engine 102 may then make a request to the URL and scan
the response received from the URL. Data 110 may be a web site or
web page containing one or more links to additional web sites, such
as shown, for example, in FIG. 1B and/or FIG. 1C. Data 110 may in
some instances be textual, a two-dimensional or three-dimensional
image, audible, or video representations, which in some instances
may entail programming code such as html, JavaScript, C, C++, or
any other programming code capable of producing text, visual
images, audio content, video content or any combination of text,
visual images, audible content and video content.
[1123] Then, operation 220 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates an Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. Effect of data
acceptability determination engine 106 (FIG. 1A) may utilize, for
example, virtual machine 12 (FIG. 1A) spawned by virtual machine
module 118 to determine whether data associated with Link 2 would
result in a change in the operating system of real machine 130
contra to a user preference regarding the operating system as
stored in the user preference database 120.
[1124] Then, operation 230 illustrates providing at least one data
display option to the end user's real machine based on the
determining acceptability of the effect of the retrieved at least a
portion of the data. FIG. 1A illustrates a data provider engine
108. Data provider engine 108 may be in communication with Effect
of data acceptability determination engine 106, which may receive
data from data retriever engine 102. Effect of data acceptability
determination engine 106 may transfer at least an effect of data
acceptability determination to the data provider engine 108 to
provide at least one data display option. In one example, data
provider engine 108 (FIG. 1A) provides data via placing the data on
a visual display, where the data is such that it meets one or more
thresholds associated with the effect of data acceptability
determination. Provided data may be a list of web links, a web
page, or other data (e.g., text, video, audio) that either have
been deemed acceptable by Effect of data acceptability
determination engine 106 or that have been modified (e.g.,
obfuscated), such as by data modification engine 122, such that the
to-be-displayed data is determined to be acceptable under user
preferences. Display option may include providing a visual display
of the data (e.g., displaying text, playing a video, etc.),
providing an audible presentation of the data (e.g., playing an
audio file), providing a mixed media display of the data (e.g.,
playing a video and an associated audio file), and so on. Provided
data may be modified via the data modification engine 122. For
instance, provided data may be obfuscated via the data obfuscation
engine 124 (e.g., at least a portion of the displayed data may be
blurred out or disabled), or provided data may be anonymized via
the data anonymization engine 126 (e.g., at least a portion of the
data may be deleted entirely). Data provider engine 108 (FIG. 1A)
may receive at least one display instruction (e.g. OK to display
links 1 and 2) from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, each of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machines 11, 12, and/or 13. Such instruction may
include an instruction to the data provider engine 108 to prevent
the data provider engine 108 from displaying data that may
configure a hardware profile of real machine 130 counter to
anti-viral settings stored in the user preference database 120
(FIG. 1A), or an instruction to the data provider engine 108 to
prevent the data provider engine 108 from displaying data that may
configure an operating system of real machine 130 counter to a
previous operating system of the real machine (130) (e.g. determine
if a rootkit has been installed).
[1125] FIG. 195 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[1126] The operation 302 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining a database of known data for
data information. Continuing the example above, data retriever
engine 102 (FIG. 1A) may retrieve data 110 retrieved from a data
source by the data retriever engine 102 and communicate data 110 to
Effect of data acceptability engine 106, which transfers data 110
to the database examination engine 112. Database examination engine
112 may be configured to examine a database of data provided, for
example, by a data provider service or a database of data stored on
a real machine 130 and compare examined database data to the
retrieved data 110. Effect of data acceptability determination
engine 106 may utilize format/protocol information to determine
whether database examination engine should call a specific database
or library (e.g., a Windows Media Player library) to obtain file
information. File information may be utilized to compare retrieved
data 110 to data stored in a library. For instance, a database may
include a list of links viewed by a user or pre-approved by a user
based on one or more user-specified preferences, such as links from
a specific source of information (e.g., the Roman Catholic Church)
and may provide an indication to the Effect of data acceptability
engine 106 that data 110 is pre-approved data.
[1127] The operation 304 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by traversing data in real time. Continuing
the example above, data retriever engine 102 (FIG. 1A) may
retrieve
[1128] data 110 retrieved from a data source by the data retriever
engine 102 and communicate data 110 to Effect of data acceptability
engine 106, which transfers data 110 to the data transverser engine
114. Data transverser engine 114 may traverse links of data 110.
For instance, data transverser engine 114 may be configured to
traverse (e.g., scan) the data 110 to determine the content of the
data (e.g., text, images, video files). Accordingly, FIG. 1B
illustrates virtual machine 11 encompassing a virtual machine
representation of real machine 130, post activation of Link 3
(e.g., representative of one or more states of one or more
hardware/software/firmware components of/resident within real
machine 130). Data traversal may occur in real time (e.g.,
simultaneously as data is loading). Upon traversal of at least a
portion of Link 3 by the data transverser engine 114, Effect of
data acceptability determination engine 106 may determine whether
an effect of the retrieved data is acceptable to a user based on a
user's preferences by comparing the traversed data to one or more
user preferences stored in a user preference database 120 (FIG.
1A).
[1129] The operation 306 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by locally examining data. For instance,
continuing the example above, Effect of data acceptability engine
106 may receive data 110 retrieved from a data source (e.g. a
computer accessible through the internet) by the data retriever
engine 102 and communicate data 110 to a local data examination
engine 116 (FIG. 1A) of virtual machine 11. Local data examination
engine 116 may extract data content information from at least a
portion of the data. Local data examination engine 116 may locally
(e.g., on the real machine 130) examine (e.g., analyze) at least a
portion of the data (e.g., one or more pointers in the data) to
determine data content (e.g., an audio file is a .wav file). For
instance, local data examination engine 116 may view an amount of
html source code to locate markers signifying the format of at
least a portion of data content. The local examination engine 116
may examine the data 110 on the real machine 130 at the location of
the real machine 130 (e.g. executed on a subsystem within an end
user's real machine) to determine data content (e.g. a downloadable
software program).
[1130] FIG. 196 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, and/or an operation
406.
[1131] The operation 402 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining data to locate references to
additional data. Continuing the example above, FIG. 1A illustrates
the Effect of data acceptability determination engine 106. Effect
of data acceptability determination engine 106 may receive data
from data retriever engine 102. FIG. 1A further illustrates the
Effect of data acceptability determination engine 106 further
including a virtual machine module 118 and a user preference
database 120. Effect of data acceptability determination engine 106
may transfer the data to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, and/or 13, and transfer the data to at least one of virtual
machines 11, 12, and/or 13 further including data transverser
engine 114 and local data examination engine 116. At least one of
virtual machines 11, 12, and/or 13 may utilize at least one of data
transverser engine 114 and local data examination engine 116 to
examine (e.g. scan) at least a portion of data (e.g. an imbedded
link on a webpage) to determine if the data references additional
data (e.g. one or more additional links). Additional data may be a
web page comprising text and/or an image, a link to a web page, a
video or any combination of text, images, links to web pages, or
videos. Virtual machines 11, 12, and/or 13 may traverse additional
data to determine an acceptability of an effect of the data. Effect
of data acceptability determination may be communicated to Effect
of data acceptability determination engine 106 that may communicate
an effect of data acceptability determination to a data provider
engine 108.
[1132] The operation 404 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by determining whether data references
additional data when loading. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer retrieved data to the virtual machine
module 118. Virtual machine module 118 (FIG. 1A) may spawn at least
one virtual machine 11, 12, and/or 13, and transfer the data to at
least one of virtual machines 11, 12, and/or 13 further including
data transverser engine 114 and local data examination engine 116.
At least one of virtual machines 11, 12, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine retrieved data in real time as it loads. For
instance, if a link to a webpage immediately (e.g. as soon as the
link is activated) references an additional link (e.g. to redirect
a user), a virtual machine 11, 12, and/or 13 may determine that
such a reference to an additional link (e.g., a pop-up, selectable
URL) has been made. Virtual machines 11, 12, and/or 13 may
determine whether data references additional data at any time when
the data is loading. Effect of data acceptability determination
engine 106 may communicate an effect of data acceptability
determination to a data provider engine 108.
[1133] The operation 406 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by issuing a request to a remote computer for
additional data information. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer retrieved data to the virtual machine
module 118. Virtual machine module 118 (FIG. 1A) may spawn at least
one virtual machine 11, 12, and/or 13 and transfer the data to at
least one of virtual machines 11, 12, and/or 13 further including
data transverser engine 114 and local data examination engine 116.
At least one of virtual machines 11, 12, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine data of an additional link or links and issue
a request to receive additional data information from the remote
computer or remote system (e.g. a computer at a geographically
distinct location). System 100 may include any number of
communication modules (not shown) configured to communicate over
local or remote communication channels to the remote server or
remote system.
[1134] FIG. 197 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 502, an operation 504, and/or an operation
506.
[1135] The operation 502 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining a copy of data from a location
geographically distinct from a location of the retrieved at least a
portion of the data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer retrieved data
to the virtual machine module 118. FIG. 1A illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data to at least one of
virtual machines 11, 12, and/or 13 to issue a request to a remote
computer to examine additional data information at the remote
location (e.g. a remote server farm). System 100 may include any
number of communication modules (not shown) configured to
communicate over local or remote communication channels to the
remote server or remote system.
[1136] The operation 504 illustrates generating a substantial
duplicate of at least a part of an end user's real machine at a
location geographically distinct from a location of the retrieved
at least a portion of the data. Continuing the example above, a
virtual machine 11, 12, and/or 13 of the real machine 130 may be
located at a geographically distinct location such as a remote
server, or a remote system configured duplicate data from the real
machine 130 and to receive and examine real machine information
transferred to the remote server or remote system. In one
embodiment, generating a substantial duplicate of at least a part
of an end user's real machine at a location geographically distinct
from a location of the retrieved at least a portion of the data may
include a remote server or remote system gathering parameters of an
end user's real machine to assist in generating a virtual duplicate
of the end user's real machine at the remote server or remote
system (e.g. hosted on, running on, or being implemented on the
remote server or remote system).
[1137] FIG. 198 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 602, an operation 604, and/or an operation
606.
[1138] The operation 602 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of a substantial
portion of an end user's real machine having one or more end-user
specified preferences. Continuing the example above, FIG. 1B
illustrates virtual machines 11, 12, and 13 including a virtual
machine representation of content of the real machine 130, software
of the real machine 130, hardware of the real machine 130, and an
operating system of the real machine 130. Virtual machines 11, 12,
and/or 13 may include most or all of at least one of the content of
the real machine 130 (e.g. a substantial portion of the text,
image, audio, and video files of the real machine), software of the
real machine 130 (e.g. a substantial portion of any program or
suite of programs installed on the real machine), hardware of the
real machine 130 (a substantial portion of the circuitry comprising
the real machine), and/or an operating system of the real machine
130 (e.g. a substantial portion of a Windows.RTM. operating system
installed on the real machine).
[1139] The operation 604 illustrates determining an acceptability
of an effect of data at least in part via a virtual machine
representation operating at a location of the retrieved at least a
portion of the data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer retrieved data
to the virtual machine module 118. FIG. 1A illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, and/or
13. FIG. 1A further illustrates the Effect of data acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
(FIG. 1A) may spawn at least one virtual machine 11, 12, and/or 13
and transfer the data to at least one of virtual machines 11, 12,
and/or 13. In one implementation, all or part of virtual machines
11, 12, and/or 13 may be generated on the real machine 130 (e.g. as
a subsystem of real machine 130). For instance, all or part of
virtual machines 11, 12, and/or 13 may be generated on a disk, a
memory chip, a core of a multi-core processor, etc. of an end
user's real machine.
[1140] FIG. 199 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 702, an operation 704, an operation 706,
and/or an operation 708.
[1141] The operation 702 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least two virtual machines 11, 12,
and/or 13, and transfer the data to at least one of virtual
machines 11, 12, and/or 13. FIG. 1B illustrates virtual machines
11, 12, and 13 encompassing a virtual machine representation of
real machine 130, post (e.g., subsequent to) activation of Link 1,
Link 2, and Link 3, respectively (e.g., as at least a part of real
machine 130 would exist had Link 1, Link 2, and/or Link 3 actually
been traversed on real machine 130). FIG. 1B further illustrates
virtual machines 11, 12, and/or 13 including a virtual machine
representation of content of the real machine 130 post activation
of Link 1, Link 2, and/or Link 3, respectively. Examples of such
content include a movie, music file, a script (e.g., Java script or
Active X control), a markup language, an email, etc. downloaded
onto real machine 130 from one or more sources associated with
activation/traversal of Link 1, Link 2, and/or Link 3. An example
of determining an acceptability of an effect of the data at least
in part via at least two virtual machine representations of at
least a part of an end user's real machine may include determining
an acceptability of an effect of the data at least in part via a
virtual machine representation of at least a portion of the content
of the real machine and a virtual machine representation of at
least a portion of hardware of the real machine, for example, the
state of virtual machine 11 and the state of virtual machine 12
after loading at least a portion of the data contained in Link
1.
[1142] The operation 704 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate core of a system comprising
at least two cores. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. As illustrated in FIGS. 1B and
1C, each of virtual machine 11, virtual machine 12, virtual machine
13, virtual machine 21, virtual machine 22, and virtual machine 23
may operate on an individual core 11, 12, 13, 31, 32, 33,
respectively, of a multi-core processor, or virtual machine 11 may
run on one core and virtual machines 12, 13 may run on the other
core of a dual core processor such as an Intel.RTM. dual core
processor and so on. The multi-core processor may include a
plurality of processor cores packaged in one processor package. The
term core as used herein may refer, for example, to a single
processor of a multiprocessor system, or to a processor core of a
multi-core processor. Multi-core processor may be utilized as
portable computers such as laptop computers, personal digital
assistants, or desktop computers, or servers, or another form of
processor based system. Combinations of these types of platforms
may be present. The multi-core system may include a multi-core
processor, each core comprising a separate address space, and
having internal to that address space.
[1143] The operation 706 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least two of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
may operate on a separate operating system at a location of the
data (e.g. executed on a subsystem, such as the virtual machine
module 118 (FIG. A) including a plurality of virtual machines 11,
12, and/or 13 (FIG. 1B) within the real machine 130).
[1144] The operation 708 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location of the retrieved at least a portion of the data.
Continuing the example above, FIG. 1A illustrates the Effect of
data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. FIG. 1B further illustrates virtual machines 11, 12,
13. In one implementation, any of virtual machines 11, 12, 13 may
be generated on the real machine 130 (e.g. as a subsystem of real
machine 130).
[1145] The operation 710 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location geographically distinct from a location of the retrieved
at least a portion of the data. Continuing the example above, FIG.
1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. At least one virtual machine,
for example virtual machine 12, may be virtual machines operating
at geographically distinct location such as a remote server, or a
remote system configured to receive and examine real machine
information transferred to the remote system and duplicate data
from the real machine 130. In some instances, each virtual machine
may be generated on one or more separate cores of a multi-core
processor. In another embodiment, determining an acceptability of
an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location geographically distinct from a location of the retrieved
at least a portion of the data may include gathering parameters of
an end user's real machine to assist in generating a virtual
duplicate of the end user's real machine at a remote location such
as a remote server or remote computing system (e.g. hosted on,
running on, or being implemented on the remote server or remote
system).
[1146] FIG. 200 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 802, an operation 804, and/or an operation
806.
[1147] The operation 802 illustrates determining a state change of
a virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. A state change (e.g., a
decrease in memory) of at least one of virtual machines 11, 12,
and/or 13 (FIG. 1B) may be determined by a component of at least
one of virtual machines 11, 12, and/or 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[1148] The operation 804 illustrates determining a state of a
virtual machine representation prior to loading at least a portion
of data. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may determine a state of at least one component (e.g.,
the hardware) of the virtual machine prior to activation (e.g.,
before) of a link. Virtual machine state may be representative of a
state for all or at least a portion of the components (e.g.,
content, software, hardware, operating system) of the real machine
130 represented by the virtual machine 11, 12, and/or 13. For
instance, at least one of virtual machines 11, 12, and/or 13 may be
determined to be free of viruses, an amount of virtual machine
memory may be measured, or a processing speed of at least one of
virtual machines 11, 12, and/or 13 may be determined. At least one
of virtual machines 11, 12, and/or 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[1149] The operation 806 illustrates determining a state of a
virtual machine representation after loading at least a portion of
data. Continuing the example above, FIG. 1A illustrates the Effect
of data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may determine a state of at least one component (e.g.,
the hardware) of the virtual machine subsequent to (e.g., after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by at least one of virtual machines 11, 12, and/or 13
after at least a portion of the data has loaded. For instance, at
least one of virtual machines 11, 12, and/or 13 may be determined
to contain a virus, an amount of virtual machine memory may be
measured, or a processing speed of at least one of virtual machines
11, 12, and/or 13 may be determined. At least one of virtual
machines 11, 12, and/or 13 may be examined to determine, for
example, if a virus or any other undesired software is present on
the machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[1150] FIG. 201 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 902.
[1151] The operation 902 illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. An undesirable state change may
be determined by examining the changes to at least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) and comparing the state change
of at least one of virtual machines 11, 12, and/or 13 to user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. 1A)
onto at least one of virtual machines 11, 12, and/or 13. An
undesirable state change may include any undesirable state change
including, but not limited to, a decrease in memory or processing
speed and/or the presence of a virus or other undesirable software
after at least a portion of the data has loaded. Undesirable state
changes may further include an undesirable transfer of information
located on at least one of virtual machines 11, 12, and/or 13 to an
external location, an undesirable transfer of data onto at least
one of virtual machines 11, 12, and/or 13 from an external location
after at least a portion of the data has loaded on at least one of
virtual machines 11, 12, and/or 13 that may result in an undesired
change in the state of content, software, hardware or an operating
system of the real machine 130 and/or an undesirable transfer of
data onto at least one of virtual machines 11, 12, and/or 13 where
at least a portion of the transferred data may be found
objectionable when viewed by a user 10.
[1152] FIG. 202 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1002, an operation 1004, and/or an
operation 1006.
[1153] The operation 1002 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences within an acceptable amount of user interface
time. Continuing the example above, FIG. 1A illustrates an Effect
of data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. Effect of data acceptability determination
engine 106 (FIG. 1A) may utilize, for example, virtual machine 12
(FIG. 1A) spawned by virtual machine module 118 to determine
whether data associated with Link 2 would result in a change in the
operating system of real machine 130 contra to a user preference
regarding the operating system as stored in the user preference
database 120. Effect of data acceptability determination may be
determined within an acceptable amount of user interface time (e.g.
a tolerable wait time for information retrieval). An acceptable
amount of user interface time may be within a range from an amount
of time approximating an instantaneous effect of data acceptability
determination to an amount of time approximating a maximum time a
user may be willing to wait for a result before abandoning a data
retrieval (e.g., a downloading webpage).
[1154] The operation 1004 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences in approximately one-tenth of a second.
Continuing the example above, Effect of data acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to a user
preference regarding the operating system as stored in the user
preference database 120. A user interface time of approximately
one-tenth of a second may approximate an acceptable amount elapsed
time for a user to feel that the Effect of data acceptability
determination engine 106 is reacting instantaneously.
[1155] The operation 1006 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences in less than approximately 1 second.
Continuing the example above, Effect of data acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to a user
preference regarding the operating system as stored in the user
preference database 120. A user interface time of less than
approximately one second may approximate an acceptable amount
elapsed time for a user to notice a delay in the Effect of data
acceptability determination without abandoning the information
retrieval.
[1156] FIG. 203 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1102, an operation 1104, and/or an
operation 1106.
[1157] The operation 1102 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to at least one user setting. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. An acceptability of an effect of the data may be
determined by determining if a state change to at least one of
virtual machines 11, 12, and/or 13 has occurred and comparing the
state change of at least one of virtual machines 11, 12, and/or 13
to user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Comparison may be made, for
example, by transferring user preference database information from
the user preference database 120 (FIG. 1A) to the virtual machine
module 118 (FIG. 1A) which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one end-user specified preference relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. At least one of virtual machines 11,
12, and/or 13 may determine an acceptability of an effect of the
data based on at least one user setting contained in a user
preference database at least a portion of which may be spawned onto
at least one of virtual machines 11, 12, and/or 13 via virtual
machine module 118 (e.g., does a website contain only images, text,
audio or visual data suitable for viewing by a user based on a
setting established by a user such as a political or cultural
preference setting). Further examples of user preferences include
specific religion or lifestyle preference, such as "return only
links relating to Roman Catholicism" or "return only links relating
to a vegan lifestyle" that may be stored in the real machine 130.
User-specific preference may also relate to user information safety
or computer safety, such as "do not display links requesting
information from my computer," or "do not display links that
transfer viruses onto my computer."
[1158] The operation 1104 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a personal user setting. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a personal user setting (e.g., "show only
automobile related data") contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. User preference database 120 may include at least one
personal user setting relating to at least one of content,
software, hardware and/or an operating system of a real machine
130. Personal user setting may be a setting input by a user that is
personal to the user, such as an information security level, a
content filter level, or a personal desirability setting such as
"show only non-religious data" or "show only automobile related
data."
[1159] The operation 1106 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a peer user setting. Continuing the example above, user
preference database 120 may include at least one peer user setting
relating to at least one of content, software, hardware and/or an
operating system of an end user's real machine 130. Peer user
setting may be a setting input by a user that is determined by a
peer group, such as a peer group determined information security
level such as "display only 100 percent secure websites", a peer
group determined data filter level such as "filter 100% of obscene
data", or a peer group desirability setting such as "show only
classical music related data" or "show only knitting related
data."
[1160] FIG. 204 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1202, and/or an operation 1204.
[1161] The operation 1202 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a corporate user setting. Continuing the example above,
at least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
compare the data received from the virtual machine module 118 (FIG.
1A) to a corporate user setting contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. User preference database 120 may include at
least one corporate user setting relating to at least one of
content, software, hardware and/or an operating system of an end
user's real machine 130. Corporate user setting may be a setting
input by a corporation that is determined to the corporation, such
as a corporate desirability setting such as "show only real-estate
related data" or "show only agricultural related data."
[1162] The operation 1204 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a work safety user setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a work safety user setting contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. User preference database 120 may
include at least one work safety user setting relating to at least
one of content, software, hardware and/or an operating system of an
end user's real machine 130. Thus, in one specific example, a
webpage or website data may be determined to be displayable if the
data satisfies a work safety user setting such as a corporate
information security level, corporate user setting, or a corporate
information content filter level corporate user setting.
[1163] FIG. 205 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1302, an operation 1304, and/or an
operation 1306.
[1164] The operation 1302 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a desirability setting. Continuing the example above,
at least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
compare the data received from the virtual machine module 118 (FIG.
1A) to a desirability setting (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a desirability setting established by a user such as a
desire to view only non-obscene material) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. User preference database 120 may
include at least one desirability setting relating to at least one
of content, software, hardware and/or an operating system of an end
user's real machine 130.
[1165] The operation 1304 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a religious desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
may compare the data received from the virtual machine module 118
to a religious desirability setting (e.g., does a website contain
only images, text, audio or visual data suitable for viewing by a
user based on a religious desirability setting established by a
user such as a desire to view only Hindu material) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. A religious desirability
setting may be include any setting regarding a major, minor, or
other religion such as Christianity, Judaism, Islam, Hinduism, and
so on.
[1166] The operation 1306 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a political desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a political desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a political desirability
setting established by a user such as a desire to view only
Democratic Party material) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A political desirability setting may include any setting
regarding a political party or affiliation (e.g., Republican,
Democratic, Libertarian, Green Party, etc.).
[1167] FIG. 206 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1402, and/or an operation 1404.
[1168] The operation 1402 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a cultural desirability setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a cultural desirability setting (e.g., does a website
contain only images, text, audio or visual data suitable for
viewing by a user based on a cultural desirability setting
established by a user such as a desire to view only materials
regarding early Mayan civilization) contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. A cultural desirability setting may include any
culturally related information such as a religious, ethnic,
regional, or heritage based cultural desirability setting or any
other cultural desirability setting.
[1169] The operation 1404 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a theme related desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a theme related desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a theme related
desirability setting established by a user such as a desire to view
only materials regarding collectible stamps) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A theme related desirability setting
may include any theme related information, such as information
relating to cars, fashion, electronics, sports, hobbies,
collector's items, or any theme or category that may be of interest
to a user.
[1170] FIG. 207 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1502.
[1171] The operation 1502 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to an age appropriateness desirability setting. Continuing
the example above, at least one of virtual machines 11, 12, and/or
13 (FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to an age appropriateness desirability setting
(e.g., does a website contain only images, text, audio or visual
data suitable for viewing by a user based on an age appropriateness
desirability setting established by a user such as a desire to view
only materials given a PG or lower rating as determined by the
Motion Picture of America Association film rating system) contained
in user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. An age appropriateness
desirability setting may include any age appropriate setting, such
as a rating threshold or a profanity threshold.
[1172] FIG. 208 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1602, an operation 1604, and/or an
operation 1606.
[1173] The operation 1602 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to at least one privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a privacy related setting (e.g., does a
website contain only images, text, audio or visual data suitable
for viewing by a user based on a privacy related setting
established by a user) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A privacy related setting may include any privacy
related settings (e.g., does a website contain only data that will
not request information from my computer or allow others to view
personal information saved on my computer).
[1174] The operation 1604 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a user specific privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a user specific privacy related setting
(e.g., will a website request specific information about the user
such as name, address, telephone number) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A user specific privacy related setting
may include any user specific privacy related settings (e.g., a
setting relating to a user's biographical information or financial
information).
[1175] The operation 1606 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a group privacy related setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a group privacy related setting (e.g., will a website
request information about an organization such as name, address,
telephone number) contained in user preference database information
spawned on at least one of virtual machines 11, 12, and/or 13. A
group privacy related setting may include any group privacy related
settings (e.g., a setting relating to a group's membership). Group
privacy related setting may be any setting established by a group
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting.
[1176] FIG. 209 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1702, and/or an operation 1704.
[1177] The operation 1702 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a corporate privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a corporate privacy related setting (e.g.,
will a website request information about a corporation such as data
stored on a real machine belonging to the corporation) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Corporate privacy related
setting may be determined by a corporate issued privacy manual, or
other such document or mandate set forth by officers of a
corporation.
[1178] The operation 1704 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of transmitted user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. I B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of transmitted
user information setting (e.g., do not return links that will
transmit my e-mail address, home address or telephone number to an
external location) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Acceptable type of transmitted user information setting
may be determined by a user 10 (FIG. 1B). For instance,
acceptability of the effect of the data may be determined in
response to whether or not private user information, such as credit
card numbers, bank accounts, personal identification information or
any other personal user information may be transmitted to a
location external to the real machine by selecting the link.
[1179] FIG. 210 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1802, and/or an operation 1804.
[1180] The operation 1802 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of captured user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of captured
user information setting (e.g., do not return links that will
capture my e-mail address, home address or telephone number)
contained in user preference database information spawned on at
least one of virtual machines 11, 12, and/or 13. Acceptable type of
captured user information setting may be determined by a user 10
(FIG. 1B). For instance, acceptability of the effect of the data
may be determined in response to whether or not private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information
may be captured by a machine located at a location external to the
real machine by selecting the link.
[1181] The operation 1804 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of exposed user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of exposed
user information setting (e.g., do not return links that will
expose personal financial information stored on the real machine
130) contained in user preference database information spawned on
at least one of virtual machines 11, 12, and/or 13. Acceptable
types of exposed user information settings may be determined by a
user 10 (FIG. 1B). For instance, acceptability of the effect of the
data may be determined in response to whether or not private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information
may be exposed to a machine located at a location external to the
real machine by selecting the link.
[1182] FIG. 211 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1902, an operation 1904, and/or an
operation 1906.
[1183] The operation 1902 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to visually examining a data image. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. To visually examine a data image, at least one of
virtual machines 11, 12, and/or 13 (FIG. 1B) may include an image
scanning module. In one embodiment, visually examining a data image
may include computer implemented image analysis, such as, color
analysis, pattern-matching, pattern-recognition, or any other
technique for recognizing a particular image or type of image.
[1184] The operation 1904 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of content of an end user's real machine having one or more
end-user specified preferences. Continuing the example above, FIG.
1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
further illustrates virtual machines 11, 12, and 13 including a
virtual machine representation of content of the real machine 130
post activation of Link 1, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
email, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the data at least in part via a virtual machine
representation may include determining an acceptability of an
effect of the data at least in part via a virtual machine
representation of at least a portion of the content of the real
machine include determining whether or not a video or image has
been loaded onto, for example, the virtual machine 11 after loading
at least a portion of the data contained in Link 1.
[1185] The operation 1906 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of software of an end user's real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software, such as a
state of Windows Media Player) of the real machine 130 post (e.g.,
subsequent to) activation of Link 1. Examples of such software
might include a commercial word processing program or suite of
programs (e.g., Microsoft.RTM. Office for Windows), an open source
Web browser (e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up
(e.g., an executing JavaScript.TM. and/or data obtained by same via
an XML-like scheme), a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware program (e.g., such as those of Symantec
Corporation or McAfee, Inc.), a multi-media program (e.g.,
QuickTime) etc. An example of determining an acceptability of an
effect of the data at least in part via a virtual machine
representation may include determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine include determining whether or not an unauthorized
program or suite of programs (e.g., music downloading software) has
been loaded, for example, onto virtual machine 12 after loading at
least a portion of the data contained in Link 2.
[1186] FIG. 212 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1902, an operation 2004, and/or an
operation 2006.
[1187] The operation 2002 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of hardware of an end user's real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machine 11 including a virtual machine representation of hardware
(e.g., a state of the hardware) of the real machine 130 post
activation of Link 1. Examples of such hardware might include all
or part of a chipset (e.g., data processor and/or graphics
processor chipsets such as those of Intel Corporation and/or
NvidiaCorporation), a memory chip (e.g., flash memory and/or random
access memories such as those of Sandisk Corporation and/or Samsung
Electronics, Co., LTD), a data bus, a hard disk (e.g., such as
those of Seagate Technology, LLC), a network adapter (e.g.,
wireless and/or wired LAN adapters such as those of Linksys and/or
CiscoTechnology, Inc.), printer, a removable drive (e.g., flash
drive), a cell phone, etc. An example of determining an
acceptability of an effect of the data at least in part via a
virtual machine representation includes determining an
acceptability of an effect of the data at least in part via a
virtual machine representation of at least a portion of the
hardware of the real machine includes determining whether a network
adapter on, for example, virtual machine 12 has been disabled after
loading at least a portion of the data contained in Link 2.
[1188] The operation 2004 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an operating system of an end user's real machine having
one or more end-user specified preferences. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. FIG. 1B illustrates virtual machines 11, 12, and 13
encompassing a virtual machine representation of real machine 130,
post (e.g., subsequent to) activation of Link 1, Link 2, and Link
3, respectively (e.g., as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. 1B illustrates virtual machine 11 including
a virtual machine representation of an operating system (e.g., a
state of an operating system and/or network operating system) of
the real machine 130 post activation of Link 1. Examples of such an
operating system might include a computer operating system (e.g.,
Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or a network
operating system (e.g., the Internet Operating System available
from Cisco Technology, Inc. Netware.RTM. available from Novell,
Inc., and/or Solaris available from Sun Microsystems, Inc.). An
example of determining an acceptability of an effect of the data at
least in part via a virtual machine representation includes
determining an acceptability of an effect of the data at least in
part via a virtual machine representation of at least a portion of
an operating system of the real machine include determining whether
a portion of the operating system (e.g., Microsoft Vista) on for
example, virtual machine 12 has been disabled after loading at
least a portion of the data contained in Link 2.
[1189] The operation 2006 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least a portion of a computing
device. FIG. 1D illustrates real machine 130 including at least a
part of a computing device 132. The computing device 132 may be any
device capable of processing one or more programming instructions.
For example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[1190] FIG. 213 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 2102, and/or an operation 2104.
[1191] The operation 2102 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least one peripheral device.
Continuing the example above, FIG. 1A illustrates the Effect of
data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13 that may be a virtual machine representation of at least a part
of real machine 130. Real machine 130 (FIG. 1B) may include at
least one peripheral device. For instance, FIG. 1D illustrates real
machine 130 including at least one peripheral device 134-146. FIG.
1D illustrates a representative view of an implementation of real
machine 130 (e.g., a desktop, notebook, or other type computing
system, and/or one or more peripheral devices) in which all/part of
system 100 may be implemented. FIG. 1D illustrates that
implementations of real machine 130 may include all/part of
computing device 132 and/or all/part of one or one or more
peripherals associated computing device 132.
[1192] The operation 2104 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least one peripheral device
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one of
virtual machines 11, 12, and/or 13 that may be a virtual machine
representation of at least a part of real machine 130. Real machine
130 may include at least one peripheral device. For instance, FIG.
1D illustrates an end user's real machine may also include at least
a portion of one or more peripheral devices connected/connectable
(e.g., via wired, waveguide, or wireless connections) to real
machine 130. Peripheral devices may include one or more printers
134, one or more fax machines 136, one or more peripheral memory
devices 138 (e.g., flash drive, memory stick), one or more network
adapters 139 (e.g., wired or wireless network adapters), one or
more music players 140, one or more cellular telephones 142, one or
more data acquisition devices 144 (e.g., robots) and/or one or more
device actuators 146 (e.g., a computer-controlled manufacturing
device, medical device, an hydraulic arm, a radiation emitter, or
any other component(s) of industrial/medical systems).
[1193] FIG. 214 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2202, and/or an operation 2204.
[1194] The operation 2202 illustrates providing a data display
option of displaying the retrieved at least a portion of the data.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying at least a portion of the data. For
instance, data provider engine 108 may receive at least one display
instruction (e.g., OK to display the entire text of link 1) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. Data provider engine 108 may then
display the data. Displayed data may be an unmodified web page of
text, images and/or video, or a web page including links to
additional web pages and may be displayed on an end user's real
machine display such as a computer screen.
[1195] The operation 2204 illustrates providing a data display
option of not displaying the retrieved at least a portion of the
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of not displaying at least a portion of the data.
For instance, data provider engine 108 may receive at least one do
not display instruction (e.g., Do not display the text of link 1)
from at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may include one or more
instruction generating modules configured to provide a do not
display instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the do not display instruction to the data provider
engine 108. The data display option of not displaying the data may
include a message indicated why the data is not being displayed, or
may be, for example, a blank page displayed on a display of the
real machine.
[1196] FIG. 215 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2302, an operation 2304, and/or an
operation 2306.
[1197] The operation 2302 illustrates providing a data display
option of displaying a modified version of the retrieved at least a
portion of the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of data
acceptability determination engine 106 (FIG. 1A), which may receive
data from data obtainer engine 102 (FIG. 1A). Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a modified
version of the data. For instance, data provider engine 108 (FIG.
1A) may receive at least one modify data instruction (e.g., display
only lines 1-10 of the text of link 1) from at least one component
of Effect of data acceptability determination engine 106 (FIG. 1A).
At least one of virtual machines 11, 12, and/or 13 may include one
or more instruction generating modules configured to provide a
modify data instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the modify data instruction to the data provider
engine 108. The data provider engine 108 may transmit the modify
data instruction to the data modification engine 122 for
modification of the data. Data modification engine may transmit the
modified data to the data provider engine 108. Data provider engine
108 may then display the modified version of the data. Displayed
data may be a modified web page of text, a modified image and/or a
modified video, or a modified web page including links to
additional web pages. For instance, a webpage or website may be
displaying, but any obscenities on the web page or website may
replaced by non-obscene word alternatives.
[1198] The operation 2304 illustrates providing a data display
option of obfuscating an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of data acceptability determination
engine 106 (FIG. 1A), which may receive data from data obtainer
engine 102 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
to the data provider engine 108 to provide the data display option
of obfuscating (e.g., blurring) a portion of the data (e.g.,
obscene photos). For instance, data provider engine 108 may receive
at least one obfuscate data instruction (e.g., display only
non-obscene portions of the image in link 1) from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 (FIG.
1B) may include one or more instruction generating modules
configured to provide an obfuscate data instruction to the Effect
of data acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the obfuscate data
instruction to the data provider engine 108. The data provider
engine 108 may transmit the obfuscate data instruction to the data
modification engine 122 which may transmit the obfuscate data
instruction to the data obfuscation engine 124. Data obfuscation
engine 124 may transmit the obfuscated data to the data
modification engine 122 for transmission to the data provider
engine 108. Data provider engine 108 may then display the
obfuscated version of the data. For example, obfuscating logic may
obfuscate restricted data or imagery within a webpage or image.
Obfuscation may include blurring or blocking of the objectionable
data portion.
[1199] The operation 2306 illustrates providing a data display
option of anonymizing an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of data acceptability determination
engine 106 (FIG. 1A), which may receive data from data obtainer
engine 102 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
and an instruction to the data provider engine 108 to provide the
data display option of anonymizing (e.g., obscuring source
information) for a portion of the data (e.g., graphic videos). For
instance, data provider engine 108 may receive at least one
anonymize data instruction (e.g., obscure source information for
portions of the video in link 1) from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide an
anonymize data instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the anonymize data instruction to the data provider
engine 108. The data provider engine 108 may transmit the anonymize
data instruction to the data modification engine 122 which may
transmit the anonymize data instruction to the data anonymization
engine 126. Data anonymization engine 126 may transmit the
anonymized data to the data modification engine 122 for
transmission to the data provider engine 108. Data provider engine
108 may then display the anonymized version of the data. Anonymized
data may be data in which the original identity information of the
data is hidden, obscured, replaced, and/or otherwise modified.
[1200] FIG. 216 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2402, an operation 2404, and/or an
operation 2406.
[1201] The operation 2402 illustrates providing a data display
option of removing, altering, or replacing an objectionable data
portion. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination and an instruction to the data provider engine 108 to
provide the data display option of removing, altering or replacing
an objectionable data portion (e.g., replacing profanity with
innocuous language) for a portion of the data (e.g., explicit
lyrics). For instance, data provider engine 108 may receive at
least one alter, remove or replace instruction (e.g., obscure
source information for portions of the video in link 1) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the remove, alter or
replace data instruction to the data provider engine 108. The data
provider engine 108 may transmit the anonymize data instruction to
the data modification engine 122 which may then remove, alter or
replace the data. Data modification engine 122 may transmit the
data containing removed, altered or replaced portions to the data
provider engine 108. Data provider engine 108 may then display the
data containing removed, altered, or replaced portions. Thus, in
one specific example, a portion of a webpage produced by a search
including data relating to religions other than Catholicism may be
removed from the web page prior to display of the data on an end
user's real machine display such as a computer screen.
[1202] The operation 2404 illustrates providing a data display
option of displaying a data portion consistent with at least one
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a setting stored, for example, in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If displayed data needs to be
modified to be consistent with at least one setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 (FIG. 1A) may transmit the
modified data to the data provider engine 108. Data provider engine
108 may then display the data consistent with the setting. Thus, a
webpage or website data may be determined to be displayable if the
data satisfies a setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the setting. For instance, a
portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate setting.
[1203] The operation 2406 illustrates providing a data display
option of displaying a data portion consistent with a privacy
related setting. Continuing the example above, at least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a privacy related
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, and/or 13. Effect of
data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one
privacy related setting, the data provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data consistent with the privacy related setting. For instance, a
portion of a returned webpage including data requesting private
user information such as a user's social security number or e-mail
address may be removed from the web page prior to display of the
data on a computer screen. Further specific examples include a
webpage or website data may be determined to be displayable if the
data satisfies a setting such as a privacy related setting such as
a setting relating to a user's biographical information or
financial information, a webpage or website data may be determined
to be displayable if the data satisfies a group privacy related
setting such as a work group (e.g., employees of a company), a peer
group (e.g., members of a book club), or a family group (e.g.,
members of family unit) privacy related setting, or a webpage or
website data may be determined to be displayable if the data
satisfies a privacy setting determined by a corporation or other
organization to maintain corporate or organization privacy.
[1204] FIG. 217 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2502.
[1205] The operation 2502 illustrates providing a data display
option of displaying a data portion consistent with a user setting.
Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one user
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one user setting, the data provider engine
108 (FIG. 1A) may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 (FIG. 1A) may transmit the modified data to
the data provider engine 108. Data provider engine 108 may then
display the data consistent with the user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a user setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the user setting. For instance,
a portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[1206] FIG. 218 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2602.
[1207] The operation 2602 illustrates providing a data display
option of displaying a data portion consistent with a desirability
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If displayed data
needs to be modified to be consistent with at least one
desirability setting, the data provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data portion consistent with the desirability setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[1208] FIG. 219 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2702.
[1209] The operation 2702 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, at least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, and/or 13. Effect of
data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one
workplace established setting, the data provider engine 108 (FIG.
1A) may transmit the modify data instruction to the data
modification engine 122 (FIG. 1A) for modification of the data.
Data modification engine 122 may transmit the modified data to the
data provider engine 108. Data provider engine 108 may then display
the data portion consistent with the workplace established setting.
For instance, the data display option may be displaying on a
display of an end user's real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[1210] FIG. 220 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2802, and/or an operation 2804.
[1211] The operation 2802 illustrates providing a data display
option of displaying a data portion consistent with a safety
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If displayed data needs to be
modified to be consistent with at least one safety setting, the
data provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data provider engine 108. Data provider
engine 108 may then display the data portion consistent with the
safety setting. For instance, the data display option may be
displaying on a display of an end user's real machine only a data
portion consistent with child safety setting such as "display only
non-violent data," or "display only ethnic and gender neutral
data."
[1212] The operation 2804 illustrates providing a data display
option of displaying a data portion consistent with a public safety
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If displayed data
needs to be modified to be consistent with at least one public
safety setting, the data provider engine 108 (FIG. 1A) may transmit
the modify data instruction to the data modification engine 122
(FIG. 1A) for modification of the data. Data provider engine 108
may then display the data portion consistent with the public safety
setting. For instance, the data display option may be displaying on
a display of an end user's real machine only a data portion
consistent with public safety setting such as "display only
non-confidential data."
[1213] FIG. 221 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2902.
[1214] The operation 2902 illustrates providing a data display
option of displaying a data portion consistent with a home safety
setting. Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one home
safety setting. For instance, data provider engine 108 may receive
at least one display instruction from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a home
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, and/or 13. Effect
of data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one home
safety setting, the data provider engine 108 (FIG. 1A) may transmit
the modify data instruction to the data modification engine 122
(FIG. 1A) for modification of the data. Data provider engine 108
may then display the data portion consistent with the home safety
setting. For instance, the data display option may be displaying on
a display of an end user's real machine only a data portion
consistent with home safety setting such as "okay to display
private or confidential data."
[1215] FIG. 222 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3002.
[1216] The operation 3002 illustrates providing a data display
option of displaying a data portion consistent with a workplace
safety setting. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data provider
engine 108 may receive at least one display instruction from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a workplace safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one workplace safety setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data provider engine 108 may then display
the data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
workplace safety setting such as "display only non-personal
data."
[1217] FIG. 223 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3102.
[1218] The operation 3102 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
child safety setting. For instance, data provider engine 108 may
receive at least one display instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a child safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one child safety setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data provider engine 108 may then display
the data portion consistent with the child safety setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
child safety setting such as "display only non-violent data."
[1219] FIG. 224 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3202, an operation 3204, and/or an
operation 3206.
[1220] The operation 3202 illustrates redirecting to alternative
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. I A), which may receive data from
data retriever engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108, and an instruction
to provide the data display option of redirecting to alternative
data (e.g., another website). For instance, data provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). Each of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide a
redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect instruction to the data provider
engine 108. The data provider engine 108 may transmit the redirect
data instruction to the data redirection engine 128 for redirection
to alternative data. The data redirection engine 128 may transmit
the redirection to the data provider engine 108. Data provider
engine 108 may then display the alternative data.
[1221] The operation 3204 illustrates automatically redirecting to
alternative data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of automatically redirecting to
alternative data (e.g., another website) consistent with a user
preference. For instance, data provider engine 108 may receive at
least one automatically redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an automatically redirect instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate an automatically redirect
to alternative data consistent with the user preference instruction
to the data provider engine 108. The data provider engine 108 may
transmit the redirect instruction to the data redirection engine
128 for automatic redirection to alternative data consistent with
the user preference. The data redirection engine 128 may transmit
the automatic redirection to the data provider engine 108. Data
provider engine 108 may then automatically (e.g., prior to alerting
a user) display the alternative data. For instance, an end user's
real machine 130 may be automatically redirected to an acceptable
web link, or a page of acceptable data.
[1222] The operation 3206 illustrates providing a list of
selectable alternative data options. Continuing the example above,
Effect of data acceptability determination engine 106 may transfer
effect of data acceptability determination to the data provider
engine 108, and an instruction to provide the data display option
of providing a list of selectable alternative data options (e.g., a
list of alternative websites) consistent with a user preference.
For instance, data provider engine 108 may receive at least one
provide selectable alternatives instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
transmit a provide selectable alternatives instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data provider engine 108. The data
provider engine 108 may transmit the provide selectable
alternatives instruction to the data redirection engine 128 to
provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data provider engine 108. Data
provider engine 108 may then display the list of selectable
alternatives. For instance, the list of selectable alternative data
options may include a list of acceptable web links or a selectable
list of web pages. Selectable web links and web pages may include a
thumbnail image of the first page of the web link or of the web
page.
[1223] FIG. 225 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3302, and/or an operation 3304.
[1224] The operation 3302 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one privacy
related setting. For instance, data provider engine 108 may receive
at least one display instruction (e.g., OK to display webpage) from
at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a privacy related setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If data needs to be
modified to be consistent with at least one privacy related
setting, the data provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data provider engine 108. Data provider engine 108 may
then display the data consistent with the privacy related setting.
For instance, a portion of a returned webpage including data
requesting private user information such as a user's social
security number or e-mail address may be removed from the web page
prior to display of the data on a computer screen. Further specific
examples include a webpage or website data may be determined to be
displayable if the data satisfies a setting such as a privacy
related setting such as a setting relating to a user's biographical
information or financial information, a webpage or website data may
be determined to be displayable if the data satisfies a group
privacy related setting such as a work group (e.g., employees of a
company), a peer group (e.g., members of a book club), or a family
group (e.g., members of family unit) privacy related setting, or a
webpage or website data may be determined to be displayable if the
data satisfies a privacy setting determined by a corporation or
other organization to maintain corporate or organization
privacy.
[1225] The operation 3304 illustrates displaying alternative data
consistent with a customized user setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one customized
user setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a customized user setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one customized user setting, the data
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data consistent with the customized user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a customized user setting when at least one of virtual
machines 11, 12, and/or 13 compares the data to the customized user
setting. For instance, a portion of a webpage produced by a search
including non-English text may be removed from the web page prior
to display of the data on a computer screen. Further, in one
specific example, a webpage or website data may be determined to be
displayable if the data satisfies a customized peer user setting,
or a webpage or website data may be determined to be displayable if
the data satisfies, for instance, a customized corporate user
setting.
[1226] FIG. 226 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3402.
[1227] The operation 3402 illustrates displaying alternative data
consistent with a desirability setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one desirability
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display image) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one desirability setting, the data
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data portion consistent with the desirability setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[1228] FIG. 227 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3502, an operation 3504, and/or an
operation 3506.
[1229] The operation 3502 illustrates displaying alternative data
consistent with a workplace established setting. Continuing the
example above, data provider engine 108 may receive at least one
display instruction (e.g., do not display data) from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a workplace established setting stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one workplace established setting, the
data provider engine 108 may transmit the modify data instruction
to the data modification engine 122 for modification of the data.
Data modification engine 122 may transmit the modified data to the
data provider engine 108. Data provider engine 108 may then display
the data portion consistent with the workplace established setting.
For instance, the data display option may be displaying on a
display of an end user's real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[1230] The operation 3504 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a user
history setting (e.g., another website). For instance, data
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user history setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a user history setting
instruction to the data provider engine 108. The data provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data. For
instance, displayed alternative data may be consistent with a user
history such as having viewed only music related data and
pages.
[1231] The operation 3506 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
Effect of data acceptability determination engine 106 may transfer
effect of data acceptability determination to the data provider
engine 108, and an instruction to provide the data display option
of redirecting to alternative data consistent with a safety setting
(e.g., another website). For instance, data provider engine 108 may
receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect to alternative data consistent with a
safety setting instruction to the data provider engine 108. The
data provider engine 108 may transmit the redirect data instruction
to the data redirection engine 128 for redirection to alternative
data consistent with a safety setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a safety setting may
include displaying a different webpage including only information
consistent with a safety setting such as "do not display links
requesting credit card information."
[1232] FIG. 228 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3602, and/or an operation 3604.
[1233] The operation 3602 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a
workplace safety setting (e.g., another website). For instance,
data provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect to alternative data consistent with a
workplace safety setting instruction to the data provider engine
108. The data provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace safety setting. The
data redirection engine 128 may transmit the redirection to the
data provider engine 108. Data provider engine 108 may then display
the alternative data. Displaying alternative data consistent with a
workplace safety setting may include displaying a different webpage
including only information consistent with a workplace safety
setting such as "do not display links requesting information on
this computer."
[1234] The operation 3604 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g., another website). For instance, data provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a child safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a child safety setting instruction to the data
provider engine 108. The data provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a child safety
setting. The data redirection engine 128 may transmit the
redirection to the data provider engine 108. Data provider engine
108 may then display the alternative data. Displaying alternative
data consistent with a child safety setting may include displaying
a different webpage including only information consistent with a
child safety setting such as "do not display links containing
trailers for rated `R` movies."
[1235] FIG. 229 illustrates alternative embodiments of the example
operational flow 200G of FIG. 193 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3702, and/or an operation 3704.
[1236] The operation 3702 illustrates displaying alternative data
consistent with a public safety setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a public safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a public safety setting instruction to the data
provider engine 108. The data provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a public safety
setting. The data redirection engine 128 may transmit the
redirection to the data provider engine 108. Data provider engine
108 may then display the alternative data. Displaying alternative
data consistent with a public safety setting may include displaying
a different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[1237] The operation 3704 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a public
safety setting (e.g., another website). For instance, data provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
to the data provider engine 108, and an instruction to provide the
data display option of redirecting to alternative data consistent
with a home safety setting (e.g., another website). For instance,
data provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a home
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, and/or 13. Effect
of data acceptability determination engine 106 may communicate the
redirect to alternative data consistent with a home safety setting
instruction to the data provider engine 108. The data provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a home safety setting
may include displaying a different webpage including only
information consistent with a home safety setting such as "do not
display links requesting address information."
Application Ser. No. 13/914,279 (1206-003-007C1-C10001)
[1238] FIG. 230 illustrates an operational flow 200H representing
example operations. After a start operation, the operational flow
200H moves to an operation 210. Operation 210 illustrates
retrieving at least a portion of data from a data source (e.g., a
computer accessible from the internet). For example, FIG. 1A
illustrates a data retriever engine 102. Data retriever engine 102
may retrieve (e.g. download) data 110 (e.g. a web page) from a data
source such as a computer accessible from the internet. For
example, data retriever engine 102 may set a URL and add a query
string value to the URL. Data retriever engine 102 may then make a
request to the URL and scan the response received from the URL.
Data 110 may be a web site or web page containing one or more links
to additional web sites, such as shown, for example, in FIG. 1B
and/or FIG. 1C, Data 110 may in some instances be textual, a
two-dimensional or three-dimensional image, audible, or video
representations, which in some instances may entail programming
code such as html, JavaScript, C, C++, or any other programming
code capable of producing text, visual images, audio content, video
content or any combination of text, visual images, audible content
and video content,
[1239] Then, operation 220 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates an Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. Effect of data
acceptability determination engine 106 (FIG. 1A) may utilize, for
example, virtual machine 12 (FIG. 1A) spawned by virtual machine
module 118 to determine whether data associated with Link 2 would
result in a change in the operating system of real machine 130
contra to a user preference regarding the operating system as
stored in the user preference database 120.
[1240] Then, operation 230 illustrates providing at least one data
display option to the end user's real machine based on the
determining acceptability of the effect of the retrieved at least a
portion of the data. FIG. 1A illustrates a data provider engine
108. Data provider engine 108 may be in communication with Effect
of data acceptability determination engine 106, which may receive
data from data retriever engine 102. Effect of data acceptability
determination engine 106 may transfer at least an effect of data
acceptability determination to the data provider engine 108 to
provide at least one data display option. In one example, data
provider engine 108 (FIG. I A) provides data via placing the data
on a visual display, where the data is such that it meets one or
more thresholds associated with the effect of data acceptability
determination. Provided data may be a list of web links, a web
page, or other data (e.g., text, video, audio) that either have
been deemed acceptable by Effect of data acceptability
determination engine 106 or that have been modified (e.g.,
obfuscated), such as by data modification engine 122, such that the
to-be-displayed data is determined to be acceptable under user
preferences. Display option may include providing a visual display
of the data (e.g. displaying text, playing a video, etc.),
providing an audible presentation of the data (e.g., playing an
audio tile), providing a mixed media display of the data (e.g.,
playing a video and an associated audio file), and so on. Provided
data may be modified via the data modification engine 122. For
instance, provided data may be obfuscated via the data obfuscation
engine 124 (e.g., at least a portion of the displayed data may be
blurred out or disabled), or provided data may be anonymized via
the data anonymization engine 126 (e.g., at least a portion of the
data may be deleted entirely). Data provider engine 108 (FIG. 1A)
may receive at least one display instruction (e.g. OK to display
links I and 2) from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A) for at least a
portion of data to be displayed. For instance, each of virtual
machines 11. 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. I A) spawned on
the virtual machines 11, 12, and/or 13. Such instruction may
include an instruction to the data provider engine 108 to prevent
the data provider engine 108 from displaying data that may
configure a hardware profile of real machine 130 counter to
anti-viral settings stored in the user preference database 120 (IG.
I A), or an instruction to the data provider engine 108 to prevent
the data provider engine 108 from displaying data that may
configure an operating system of real machine 130 counter to a
previous operating system of the real machine (130) (e.g. determine
if a rootkit has been installed).
[1241] FIG. 231 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 302, an operation 304, and/or an operation
306.
[1242] The operation 302 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining a database of known data for
data information. Continuing the example above, data retriever
engine 102 (FIG. 1A) may retrieve data 110 retrieved from a data
source by the data retriever engine 102 and communicate data 110 to
Effect of data acceptability engine 106, which transfers data 110
to the database examination engine 112. Database examination engine
112 may be configured to examine a database of data provided, for
example, by a data provider service or a database of data stored on
a real machine 130 and compare examined database data to the
retrieved data 110. Effect of data acceptability determination
engine 106 may utilize format/protocol information to determine
whether database examination engine should call a specific database
or library (e.g., a Windows Media Player library) to obtain file
information. File information may be utilized to compare retrieved
data 110 to data stored in a library. For instance, a database may
include a list of links viewed by a user or pre-approved by a user
based on one or more user-specified preferences, such as links from
a specific source of information (e.g., the Roman Catholic Church)
and may provide an indication to the Effect of data acceptability
engine 106 that data 110 is pre-approved data.
[1243] The operation 304 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by traversing data in real time. Continuing
the example above, data retriever engine 102 (FIG. 1A) may retrieve
data 110 retrieved from a data source by the data retriever engine
102 and communicate data 110 to Effect of data acceptability engine
106, which transfers data 110 to the data transverser engine 114.
Data transverser engine 114 may traverse links of data 110. For
instance, data transverser engine 114 may be configured to traverse
(e.g., scan) the data 110 to determine the content of the data
(e.g., text, images, video files). Accordingly, FIG. 1B illustrates
virtual machine 11 encompassing a virtual machine representation of
real machine 130, post activation of Link 3 (e.g., representative
of one or more states of one or more hardware/software/firmware
components of/resident within real machine 130). Data traversal may
occur in real time (e.g., simultaneously as data is loading). Upon
traversal of at least a portion of Link 3 by the data transverser
engine 114, Effect of data acceptability determination engine 106
may determine whether an effect of the retrieved data is acceptable
to a user based on a user's preferences by comparing the traversed
data to one or more user preferences stored in a user preference
database 120 (FIG. 1A).
[1244] The operation 306 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by locally examining data. For instance,
continuing the example above, Effect of data acceptability engine
106 may receive data 110 retrieved from a data source (e.g. a
computer accessible through the Internet) by the data retriever
engine 102 and communicate data 110 to a local data examination
engine 116 (FIG. 1A) of virtual machine 11. Local data examination
engine 116 may extract data content information from at least a
portion of the data. Local data examination engine 116 may locally
(e.g., on the real machine 130) examine (e.g., analyze) at least a
portion of the data (e.g., one or more pointers in the data) to
determine data content (e.g., an audio file is a .wav file). For
instance, local data examination engine 116 may view an amount of
html source code to locate markers signifying the format of at
least a portion of data content. The local examination engine 116
may examine the data 110 on the real machine 130 at the location of
the real machine 130 (e.g. executed on a subsystem within an end
user's real machine) to determine data content (e.g. a downloadable
software program).
[1245] FIG. 232 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 402, an operation 404, and/or an operation
406.
[1246] The operation 402 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining data to locate references to
additional data. Continuing the example above, FIG. 1A illustrates
the Effect of data acceptability determination engine 106. Effect
of data acceptability determination engine 106 may receive data
from data retriever engine 102. FIG. 1A further illustrates the
Effect of data acceptability determination engine 106 further
including a virtual machine module 11$ and a user preference
database 120. Effect of data acceptability determination engine 106
may transfer the data to the virtual machine module 118. Virtual
machine module 118 (FIG. 1A) may spawn at least one virtual machine
11, 12, anal/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13 further including data
transverser engine 114 and local data examination engine 116. At
least one of virtual machines 11, 12, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine (e.g. scan) at least a portion of data (e.g.
an imbedded link on a webpage) to determine if the data references
additional data (e.g. one or more additional links). Additional
data may be a web page comprising text and/or an image, a link to a
web page, a video or any combination of text, images, links to web
pages, or videos. Virtual machines 11, 12, and/or 13 may traverse
additional data to determine an acceptability of an effect of the
data. Effect of data acceptability determination may be
communicated to Effect of data acceptability determination engine
106 that may communicate an effect of data acceptability
determination to a data provider engine 108.
[1247] The operation 404 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by determining whether data references
additional data when loading. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer retrieved data to the virtual machine
module 118. Virtual machine module 118 (FIG. 1A) may spawn at least
one virtual machine 11, 12, and/or 13, and transfer the data to at
least one of virtual machines 11, 12, and/or 13 further including
data transverser engine 114 and local data examination engine 116.
At least one of virtual machines 11, 1.2, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine retrieved data in real time as it loads. For
instance, if a link to a webpage immediately (e.g. as soon as the
link is activated) references an additional link (e.g. to redirect
a user), a virtual machine 11, 12, and/or 13 may determine that
such a reference to an additional link (e.g., a pop-up, selectable.
URL) has been made. Virtual machines 11, 12, and/or 13 may
determine whether data references additional data at any time when
the data is loading. Effect of data acceptability determination
engine 106 may communicate an effect of data acceptability
determination to a data provider engine 108.
[1248] The operation 406 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by issuing a request to a remote computer for
additional data information. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer retrieved data to the virtual machine
module 118. Virtual machine module 118 (FIG. 1A) may spawn at least
one virtual machine 11, 12, and/or 13 and transfer the data to at
least one of virtual machines 11, 12, and/or 13 further including
data transverser engine 114 and local data examination engine 116.
At least one of virtual machines 11, 12, and/or 13 may utilize at
least one of data transverser engine 114 and local data examination
engine 116 to examine data of an additional link or links and issue
a request to receive additional data information from the remote
computer or remote system (e.g. a computer at a geographically
distinct location). System 100 may include any number of
communication modules (not shown) configured to communicate over
local or remote communication channels to the remote server or
remote system.
[1249] FIG. 233 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 502, an operation 504, and/or an operation
506.
[1250] The operation 502 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences by examining a copy of data from a location
geographically distinct from a location of the retrieved at least a
portion of the data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer retrieved data
to the virtual machine module 118. FIG. 1A illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13 and transfer the data to at least one of
virtual machines 11, 12, and/or 13 to issue a request to a remote
computer to examine additional data information at the remote
location (e.g. a remote server farm). System 100 may include any
number of communication modules (not shown) configured to
communicate over local or remote communication channels to the
remote server or remote system.
[1251] The operation 504 illustrates generating a substantial
duplicate of at least a part of an end user's real machine at a
location geographically distinct from a location of the retrieved
at least a portion of the data. Continuing the example above, a
virtual machine 11, 12, and/or 13 of the real machine 130 may be
located at a geographically distinct location such as a remote
server, or a remote system configured duplicate data from the real
machine 130 and to receive and examine real machine information
transferred to the remote server or remote system. In one
embodiment, generating a substantial duplicate of at least a part
of an end user's real machine at a location geographically distinct
from a location of the retrieved at least a portion of the data may
include a remote server or remote system gathering parameters of an
end user's real machine to assist in generating a virtual duplicate
of the end user's real machine at the remote server or remote
system (e.g. hosted on, running on, or being implemented on the
remote server or remote system).
[1252] FIG. 234 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 602, an operation 604, and/or an operation
606.
[1253] The operation 602 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of a substantial
portion of an. cud user's real machine having one or more end-user
specified preferences. Continuing the example above, FIG. 313
illustrates virtual machines 11, 12, and 13 including a virtual
machine representation of content of the real machine 130, software
of the real machine 130, hardware of the real machine 130, and an
operating system of the real machine 130. Virtual machines 11, 12,
and/or 13 may include most or all of at least one of the content of
the real machine 130 (e.g. a substantial portion of the text,
image, audio, and video files of the real machine), software of the
real machine 130 (e.g. a substantial portion of any program or
suite of programs installed on the real machine), hardware of the
real machine 130 (a substantial portion of the circuitry comprising
the real machine), and/or an operating system of the real machine
130 (e.g. a substantial portion of a Windows.RTM. operating system
installed on the real machine).
[1254] The operation 604 illustrates determining an acceptability
of an effect of data at least in part via a virtual machine
representation operating at a location of the retrieved at least a
portion of the data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer retrieved data
to the virtual machine module 118. FIG. 1A illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Virtual machine module 118 includes virtual machines 11, 12, and/or
13. FIG. 1A further illustrates the Effect of data acceptability
determination engine 106 further including a virtual machine module
118 and a user preference database 120. Virtual machine module 118
(FIG. 1A) may spawn at least one virtual machine 11, 12, and/or 13
and transfer the data to at least one of virtual machines 11, 12,
and/or 13. In one implementation, all or part of virtual machines
11, 12, and/or 13 may be generated on the real machine 130 (e.g. as
a subsystem of real machine 130), For instance, all or part of
virtual machines 11, 12, and/or 13 may he generated on a disk, a
memory chip, a core of a multi-core processor, etc. of an end
user's real machine.
[1255] FIG. 235 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 702, an operation 704, an operation 706,
and/or an operation 708.
[1256] The operation 702 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least two virtual machines 11, 12.
and/or 13, and transfer the data to at least one of virtual
machines 11, 12, and/or 13. FIG. 1B illustrates virtual machines
11, and 13 encompassing a virtual machine representation of real
machine 130, post (e.g., subsequent to) activation of Link 1, Link
2, and Link 3, respectively (e.g., as at least a part of real
machine 130 would exist had Link 1, Link 2, and/or Link 3 actually
been traversed on real machine 130). FIG. I B further illustrates
virtual machines 11. 12, and/or 13 including a virtual machine
representation of content of the real machine 130 post activation
of Link 1, Link 2, and/or Link 3, respectively. Examples of such
content include a movie, music file, a script (e.g., Java script or
Active X control), a markup language, an email, etc. downloaded
onto real machine 130 from one or more sources associated with
activation/traversal of Link 1, Link 2, and/or Link 3. An example
of determining an acceptability of an effect of the data at least
in part via at least two virtual machine representations of at
least a part of an end user's real machine may include determining
an acceptability of an effect of the data at least in part via a
virtual machine representation of at least a portion of the content
of the real machine and a virtual machine representation of at
least a portion of hardware of the real machine, for example, the
state of virtual machine 11 and the state of virtual machine 12
after loading at least a portion of the data contained in Link
1,
[1257] The operation 704 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate core of a system comprising
at least two cores. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. As illustrated in FIGS. 1B and
1C, each of virtual machine 11, virtual machine 12, virtual machine
13, virtual machine 21, virtual machine 22, and virtual machine 23
may operate on an individual core 11, 12, 13, 31, 32, 33,
respectively, of a multi-core processor, or virtual machine 11 may
run on one core and virtual machines 12, 13 may run on the other
core of a dual core processor such as an Intel.RTM. dual core
processor and so on. The multi-core processor may include a
plurality of processor cores packaged in one processor package. The
term core as used herein may refer, for example, to a single
processor of a multiprocessor system, or to a processor core of a
multi-core processor. Multi-core processor may be utilized as
portable computers such as laptop computers, personal digital
assistants, or desktop computers, or servers, or another form of
processor based system. Combinations of these types of platforms
may be present. The multi-core system may include a multi-core
processor, each core comprising a separate address space, and
having internal to that address space.
[1258] The operation 706 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least two of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
may operate on a separate operating system at a location of the
data (e.g. executed on a subsystem, such as the virtual machine
module 118 (FIG. A) including a plurality of virtual machines 11,
0.12, and/or 13 (FIG. I B) within the real machine 130).
[1259] The operation 708 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location of the retrieved at least a portion of the data.
Continuing the example above, FIG. 1A illustrates the Effect of
data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. FIG. 1B further illustrates virtual machines 11, 12,
13. In one implementation, any of virtual machines 11, 12, 13 may
be generated on the real machine 130 (e.g. as a subsystem of real
machine 130).
[1260] The operation 710 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location geographically distinct from a location of the retrieved
at least a portion of the data. Continuing the example above, FIG.
1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. At least one virtual machine,
for example virtual machine 12, may be virtual machines operating
at geographically distinct location such as a remote server, or a
remote system configured to receive and examine real machine
information transferred to the remote system and duplicate data
from the real machine 130. In some instances, each virtual machine
may be generated on one or more separate cores of a multi-core
processor. In another embodiment, determining an acceptability of
an effect of the retrieved at least a portion of the data on at
least two virtual machine representations of at least a part of an
end user's real machine having one or more end-user specified
preferences, at least one of the at least two virtual machine
representations operating on a separate operating system at a
location geographically distinct from a location of the retrieved
at least a portion of the data may include gathering parameters of
an end user's real machine to assist in generating a virtual
duplicate of the end user's real machine at a remote location such
as a remote server or remote computing system (e.g. hosted on,
running on, or being implemented on the remote server or remote
system).
[1261] FIG. 236 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 802, an operation 804, and/or an operation
806.
[1262] The operation 802 illustrates determining a state change of
a virtual machine representation between a prior state and a
subsequent state of the virtual machine representation after
loading at least a portion of data. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120, Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. A state change (e.g., a
decrease in memory) of at least one of virtual machines 11, 12,
and/or 13 (FIG. 1B) may be determined by a component of at least
one of virtual machines 11, 12, and/or 13 measuring a
characteristic of the virtual machine representation of the
content, software, hardware or operating system of the real machine
130 before and after the at least a portion of data has loaded. For
instance, a state change may be measured after a search result
containing a plurality of web links has loaded and at least one web
link has been activated.
[1263] The operation 804 illustrates determining a state of a
virtual machine representation prior to loading at least a portion
of data. Continuing the example above, FIG. 1A illustrates the
Effect of data acceptability determination engine 106. Effect of
data acceptability determination engine 106 may receive data from
data retriever engine 102. FIG. 1A further illustrates the Effect
of data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13, and transfer the data to at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 113) may determine a state of at least one component (e.g.,
the hardware) of the virtual machine prior to activation (e.g.,
before) of a link. Virtual machine state may be representative of a
state for all or at least a portion of the components (e.g.,
content, software, hardware, operating system) of the real machine
130 represented by the virtual machine 11, 12, and/or 13. For
instance, at least one of virtual machines 11, 12, and/or 13 may be
determined to be free of viruses, an amount of virtual machine
memory may be measured, or a processing speed of at least one of
virtual machines 11, 12, and/or 13 may be determined. At least one
of virtual machines 11, 12, and/or 13 may contain a diagnostic
application configured to analyze virtual machine performance and
contents.
[1264] The operation 806 illustrates determining a state of a
virtual machine representation after loading at least a portion of
data. Continuing the example above, FIG. 1A illustrates the Effect
of data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 12, and/or 13,
and transfer the data to at least one of virtual machines 11, 12,
and/or 13. At least one of virtual machines 11, 12, and/or 13 (FIG.
1B) may determine a state of at least one component (e.g., the
hardware) of the virtual machine subsequent to (e.g., after)
activation of a link. For instance a virtual machine state may be
representative of a state for all characteristics of the real
machine 130 content, software, hardware or operating system
represented by at least one of virtual machines 11, 12, and/or 13
after at least a portion of the data has loaded. For instance, at
least one of virtual machines 11, 12, and/or 13 may be determined
to contain a virus, an amount of virtual machine memory may be
measured, or a processing speed of at least one of virtual machines
11, 12, and/or 13 may be determined. At least one of virtual
machines 11, 12, and/or 13 may be examined to determine, for
example, if a virus or any other undesired software is present on
the machine after at least a portion of the data has loaded by
examining the virtual machine representation of the operating
system of the real machine 130 (FIG. 1B), or if information from
the real machine 130 has been transferred to an external location
by examining the software of the real machine 130.
[1265] FIG. 237 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 902.
[1266] The operation 902 illustrates determining whether the state
change is an undesirable state change based on one or more end-user
specified preferences. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. An undesirable state change may
be determined by examining the changes to at least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) and comparing the state change
of at least one of virtual machines 11, 12, and/or 13 to user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13 by a transfer of user preference
database information from the user preference database 120 (FIG.
1A) to the virtual machine module 118 (FIG. 1A) which spawns a copy
of at least a portion of the user preference database 120 (FIG. I
A) onto at least one of virtual machines 11, 12, and/or 13. An
undesirable state change may include any undesirable state change
including, but not limited to, a decrease in memory or processing
speed and/or the presence of a virus or other undesirable software
after at least a portion of the data has loaded. Undesirable state
changes may further include an undesirable transfer of information
located on at least one of virtual machines 11, 12, and/or 13 to an
external location, an undesirable transfer of data onto at least
one of virtual machines 11, 12, and/or 13 from an external location
after at least a portion of the data has loaded on at least one of
virtual machines 11. 12, and/or 13 that may result in an undesired
change in the state of content, software, hardware or an operating
system of the real machine 130 and/or an undesirable transfer of
data onto at least one of virtual machines 11, 12, and/or 13 where
at least a portion of the transferred data may be found
objectionable when viewed by a user 10.
[1267] FIG. 238 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1002, an operation 1004, and/or an
operation 1006.
[1268] The operation 1002 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences within an acceptable amount of user interface
time. Continuing the example above, FIG. 1A illustrates an Effect
of data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. Effect of data acceptability determination
engine 106 (FIG. 1A) may utilize, for example, virtual machine 12
(FIG. 1A) spawned by virtual machine module 118 to determine
whether data associated with Link 2 would result in a change in the
operating system of real machine 130 contra to a user preference
regarding the operating system as stored in the user preference
database 120. Effect of data acceptability determination may be
determined within an acceptable amount of user interface time (e.g.
a tolerable wait time for information retrieval). An acceptable
amount of user interface time may be within a range from an amount
of time approximating an instantaneous effect of data acceptability
determination to an amount of time approximating a maximum time a
user may be willing to wait for a result before abandoning a data
retrieval (e.g., a downloading webpage).
[1269] The operation 1004 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences in approximately one-tenth of a second.
Continuing the example above, Effect of data acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to a user
preference regarding the operating system as stored in the user
preference database 120. A user interface time of approximately
one-tenth of a second may approximate an. acceptable amount elapsed
time for a user to feel that the Effect of data acceptability
determination engine 106 is reacting instantaneously.
[1270] The operation 1006 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
part of an end user's real machine having one or more end-user
specified preferences in less than approximately 1 second.
Continuing the example above, Effect of data acceptability
determination engine 106 (FIG. 1A) may utilize, for example,
virtual machine 12 (FIG. 1A) spawned by virtual machine module 118
to determine whether data associated with Link 2 would result in a
change in the operating system of real machine 130 contra to a user
preference regarding the operating system as stored in the user
preference database 120. A user interface time of less than
approximately one second may approximate an acceptable amount
elapsed time for a user to notice a delay in the Effect of data
acceptability determination without abandoning the information
retrieval.
[1271] FIG. 239 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1102, an operation 1104, and/or an
operation 1106.
[1272] The operation 1102 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to at least one user setting. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. An acceptability of an effect of the data may be
determined by determining if a state change to at least one of
virtual machines 11, 12, and/or 13 has occurred and comparing the
state change of at least one of virtual machines 11, 12, and/or 13
to user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Comparison may be made, for
example, by transferring user preference database information from
the user preference database 120 (FIG. 1A) to the virtual machine
module 118 (FIG. 1A) which spawns a copy of at least a portion of
the user preference database 120 (FIG. 1A) onto at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one end-user specified preference relating to
at least one of content, software, hardware and/or an operating
system of a real machine 130. At least one of virtual machines 1.1,
12, and/or 13 may determine an acceptability of an effect of the
data based on at least one user setting contained in a user
preference database at least a portion of which may be spawned onto
at least one of virtual machines 11, 12, and/or 13 via virtual
machine module 118 (e.g., does a website contain only images, text,
audio or visual data suitable for viewing by a user based on a
setting established by a user such as a political or cultural
preference setting). Further examples of user preferences include
specific religion or lifestyle preference, such as "return only
links relating to Roman Catholicism" or "return only links relating
to a vegan lifestyle" that may be stored in the real machine 130.
User-specific preference may also relate to user information safety
or computer safety, such as "do not display links requesting
information from my computer," or "do not display links that
transfer viruses onto my computer."
[1273] The operation 1104 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a personal user setting. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. User preference database
information stored in the user preference database 120 (FIG. 1A)
may be transferred to the virtual machine module 118 (FIG. 1A),
which spawns a copy of at least a portion of the user preference
database 120 (FIG. 1A) onto at least one of virtual machines 11,
12, and/or 13. At least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from
[1274] the virtual machine module 118 (FIG. 1A) to a personal user
setting (e.g., "show only automobile related data") contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. User preference database 120
may include at least one personal user setting relating to at least
one of content, software, hardware and/or an operating system of a
real machine 130. Personal user setting may be a setting input by a
user that is personal to the user, such as an information security
level, a content filter level, or a personal desirability setting
such as "show only non-religious data" or "show only automobile
related data."
[1275] The operation 1106 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a peer user setting. Continuing the example above, user
preference database 120 may include at least one peer user setting
relating to at least one of content, software, hardware and/or an
operating system of an end user's real machine 130. Peer user
setting may be a setting input by a user that is determined by a
peer group, such as a peer group determined information security
level such as "display only 100 percent secure websites", a peer
group determined data filter level such as "filter 100% of obscene
data", or a peer group desirability setting such as "show only
classical music related data" or "show only knitting related
data."
[1276] FIG. 240 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1202, and/or an operation 1204.
[1277] The operation 1202 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a corporate user setting. Continuing the example above,
at least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
compare the data received from the virtual machine module 118 (FIG.
1A1 to a corporate user setting contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. User preference database 120 may include at
least one corporate user setting relating to at least one of
content, software, hardware and/or an operating system of an end
user's real machine 130. Corporate user setting may be a setting
input by a corporation that is determined to the corporation, such
as a corporate desirability setting such as "show only real-estate
related data" or "show only agricultural related data."
[1278] The operation 1204 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a work safety user setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. I A) to a work safety user setting contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. User preference database 120 may
include at least one work safety user setting relating to at least
one of content, software, hardware and/or an operating system of an
end user's real machine 130. Thus, in one specific example, a
webpage or website data may be determined to be displayable if the
data satisfies a work safety user setting such as a corporate
information security level, corporate user setting, or a corporate
information content filter level corporate user setting.
[1279] FIG. 241 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1302, an operation 1304, and/or an
operation 1306.
[1280] The operation 1302 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a desirability setting. Continuing the example above,
at least one of virtual machines 11, 12, and/or 13 (FIG. 1B) may
compare the data received from the virtual machine module 118 (FIG.
1A) to a desirability setting (e.g., does a website contain only
images, text, audio or visual data suitable for viewing by a user
based on a desirability setting established by a user such as a
desire to view only non-obscene material) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. User preference database 120 may
include at least one desirability setting relating to at least one
of content, software, hardware and/or an operating system of an end
user's real machine 130.
[1281] The operation 1304 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a religious desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
may compare the data received from the virtual machine module 118
to a religious desirability setting (e.g., does a website contain
only images, text, audio or visual data suitable for viewing by a
user based on a religious desirability setting established by a
user such as a desire to view only Hindu material) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. A religious desirability
setting may be include any setting regarding a major, minor, or
other religion such as Christianity, Judaism, Islam, Hinduism, and
so on.
[1282] The operation 1306 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a political desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a political desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a political desirability
setting established by a user such as a desire to view only
Democratic Party material) contained in user preference database
information spawned on at least one of virtual machines 11. 12,
and/or 13. A political desirability setting may include any setting
regarding a political party or affiliation (e.g., Republican
Democratic, Libertarian, Green Party, etc.).
[1283] FIG. 242 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1402, and/or an operation 1404.
[1284] The operation 1402 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a cultural desirability setting. Continuing the example
above, at least one of virtual machines 11; 12, and/or 13 (FIG.
113) may compare the data received from the virtual machine module
118 (FIG. 1A) to a cultural desirability setting (e.g., does a
website contain only images, text, audio or visual data suitable
for viewing by a user based. on a cultural desirability setting
established by a user such as a desire to view only materials
regarding early Mayan civilization) contained in user preference
database information spawned on at least one of virtual machines
11, 12, and/or 13. A cultural desirability setting may include any
culturally related information such as a religious, ethnic,
regional, or heritage based cultural desirability setting or any
other cultural desirability setting,
[1285] The operation 1404 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a theme related desirability setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a theme related desirability setting (e.g.,
does a website contain only images, text, audio or visual data
suitable for viewing by a user based on a theme related
desirability setting established by a user such as a desire to view
only materials regarding collectible stamps) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A theme related desirability setting
may include any theme related information, such as information
relating to cars, fashion, electronics, sports, hobbies,
collector's items, or any theme or category that may be of interest
to a user.
[1286] FIG. 243 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least. one additional operation. Additional operations
may include an operation 1502.
[1287] The operation 1502 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to an age appropriateness desirability setting. Continuing
the example above, at least one of virtual machines 11, 12, and/or
13 (FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to an age appropriateness desirability setting
(e.g., does a website contain only images, text, audio or visual
data suitable for viewing by a user based on an age appropriateness
desirability setting established by a user such as a desire to view
only materials given a PG or lower rating as determined by the
Motion Picture of America Association film rating system) contained
in user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. An age appropriateness
desirability setting may include any age appropriate setting, such
as a rating threshold or a profanity threshold.
[1288] FIG. 244 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1602, an operation 1604, and/or an
operation 1606.
[1289] The operation 1602 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to at least one privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a privacy related setting (e.g., does a
website contain only images, text, audio or visual data suitable
for viewing by a user based on a privacy related setting
established by a user) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. A privacy related setting may include any privacy
related settings (e.g., does a website contain only data that will
not request information from my computer or allow others to view
personal information saved on my computer).
[1290] The operation 1604 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a user specific privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 113) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a user specific privacy related setting
(e.g., will a website request specific information about the user
such as name, address, telephone number) contained in user
preference database information spawned on at least one of virtual
machines 11, 12, and/or 13. A user specific privacy related setting
may include any user specific privacy related settings (e.g., a
setting, relating to a user's biographical information or financial
information).
[1291] The operation 1606 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a group privacy related setting. Continuing the example
above, at least one of virtual machines 11, 12, and/or 13 (FIG. 1B)
may compare the data received from the virtual machine module 118
(FIG. 1A) to a group privacy related setting (e.g., will a website
request information about an organization such as name, address,
telephone number) contained in user preference database information
spawned on at least one of virtual machines 11, 12, anti/or 13. A
group privacy related setting may include any group privacy related
settings (e.g., a setting relating to a group's membership). Group
privacy related setting may be any setting established by a group
such as a work group (e.g., employees of a company), a peer group
(e.g., members of a book club), or a family group (e.g., members of
family unit) privacy related setting.
[1292] FIG. 245 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1702, and/or an operation 1704.
[1293] The operation 1702 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a corporate privacy related setting. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to a corporate privacy related setting (e.g.,
will a website request information about a corporation such as data
stored on a real machine belonging to the corporation) contained in
user preference database information spawned on at least one of
virtual machines 11, 12, and/or 13. Corporate privacy related
setting may be determined by a corporate issued privacy manual, or
other such document or mandate set forth by officers of a
corporation.
[1294] The operation 1704 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of transmitted user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of transmitted
user information setting (e.g., do not return links that will
transmit my e-mail address, home address or telephone number to an
external location) contained in user preference database
information spawned on at least one of virtual machines 11, 12,
and/or 13. Acceptable type of transmitted user information setting
may be determined by a user 10 (FIG. 1B). For instance,
acceptability of the effect of the data may be determined in
response to whether or not private user information, such as credit
card numbers, bank accounts, personal identification information or
any other personal user information may be transmitted to a
location external to the real machine by selecting the link.
[1295] FIG. 246 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1802, and/or an operation 1804.
[1296] The operation 1802 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of captured user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. 1A) to at least one acceptable type of captured
user information setting (e.g., do not return links that will
capture my e-mail address, home address or telephone number)
contained in user preference database information spawned on at
least one of virtual machines 11, 12, and/or 13. Acceptable type of
captured user information setting may be determined by a user 10
(FIG. 1B). For instance, acceptability of the effect of the data
may be determined in response to whether or not private user
information, such as credit card numbers bank accounts, personal
identification information or any other personal user information
may be captured by a machine located at a location external to the
real machine by selecting the link.
[1297] The operation 1804 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to a type of exposed user information. Continuing the
example above, at least one of virtual machines 11, 12, and/or 13
(FIG. 1B) may compare the data received from the virtual machine
module 118 (FIG. I A) to at least one acceptable type of exposed
user information setting (e.g., do not return links that will
expose personal financial information stored on the real machine
130) contained in user preference database information spawned on
at least one of virtual machines 11, 12, and/or 13. Acceptable
types of exposed user information settings may be determined by a
user 10 (FIG. 1B). For instance, acceptability of the effect of the
data may be determined in response to whether or not private user
information, such as credit card numbers, bank accounts, personal
identification information or any other personal user information
may be exposed to a machine located at a location external to the
real machine by selecting the link.
[1298] FIG. 247 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1902, an operation 1904, and/or an
operation 1906.
[1299] The operation 1902 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data in
response to visually examining a data image. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. To visually examine a data image, at least one of
virtual machines 11, 12, and/or 13 (FIG. 1B) may include an image
scanning module. In one embodiment, visually examining a data image
may include computer implemented image analysis, such as, color
analysis, pattern-matching, pattern-recognition, or any other
technique for recognizing a particular image or type of image.
[1300] The operation 1904 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of content of an end user's real machine having one or more
end-user specified preferences. Continuing the example above, FIG.
1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11, 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 1B
further illustrates virtual machines 11, 12, and 13 including a
virtual machine representation of content of the real machine 130
post activation of Link I, Link 2, and/or Link 3, respectively.
Examples of such content include a movie, music file, a script
(e.g., Java script or Active X control), a markup language, an
entail, etc. downloaded onto real machine 130 from one or more
sources associated with activation/traversal of Link 1, Link 2,
and/or Link 3. An example of determining an acceptability of an
effect of the data at least in part via a virtual machine
representation may include determining an acceptability of an
effect of the data at least in part via a virtual machine
representation of at least a portion of the content of the real
machine include determining whether or not a video or image has
been loaded onto, for example, the virtual machine 11 after loading
at least a portion of the data contained in Link 1.
[1301] The operation 1906 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of software of an end user's real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 11$.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machines 11. 12, and 13 encompassing a virtual machine
representation of real machine 130, post (e.g., subsequent to)
activation of Link 1, Link 2, and Link 3, respectively (e.g., as at
least a part of real machine 130 would exist had Link 1, Link 2,
and/or Link 3 actually been traversed on real machine 130). FIG. 18
illustrates virtual machine 11 including a virtual machine
representation of software (e.g., a state of software, such as a
state of Windows Media Player) of the real machine 130 post (e.g.,
subsequent to) activation of Link 1. Examples of such software
might include a commercial word processing program or suite of
programs (e.g., Microsoft.RTM. Office for Windows), an open source
Web browser (e.g., Mozilla's Firefox.RTM. Browser), an AJAX mash up
(e.g., an executing JavaScript.TM. and/or data obtained by same via
an XML-like scheme), a commercial database management system (e.g.,
one or more of Oracle Corporation's various products), a commercial
anti-malware/spyware program (e.g., such as those of Symantec
Corporation or McAfee, Inc.), a multi-media program (e.g.,
QuickTime) etc. An example of determining an acceptability of an
effect of the data at least in part via a virtual machine
representation may include determining an acceptability of an
effect of the content of the data at least in part via a virtual
machine representation of at least a portion of the software of the
real machine include determining whether or not an unauthorized
program or suite of programs (e.g., music downloading software) has
been loaded, for example, onto virtual machine 12 after loading at
least a portion of the data contained in Link 2.
[1302] FIG. 248 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 1902, an operation 2004, and/or an
operation 2006.
[1303] The operation 2002 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of hardware of an end user's real machine having one or
more end-user specified preferences. Continuing the example above,
FIG. 1A illustrates the Effect of data acceptability determination
engine 106. Effect of data acceptability determination engine 106
may receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one virtual
machine 11, 12, and/or 13, and transfer the data to at least one of
virtual machines 11, 12, and/or 13. FIG. 1B illustrates virtual
machine 11 including a virtual machine representation of hardware
(e.g., a state of the hardware) of the real machine 130 post
activation of Link 1. Examples of such hardware might include all
or part of a chipset (e.g., data processor and/or graphics
processor chipsets such as those of Intel Corporation and/or
NvidiaCorporation), a memory chip (e.g., flash memory and/or random
access memories such as those of Sandisk Corporation and/or Samsung
Electronics, Co., LTD), a data bus, a hard disk (e.g., such as
those of Seagate Technology, LLC), a network adapter (e.g.,
wireless and/or wired LAN adapters such as those of Linksys and/or
Cisco Technology, Inc.), printer, a removable drive (e.g., flash
drive), a cell phone, etc. An example of determining an
acceptability of an effect of the data at least in part via a
virtual machine representation includes determining an
acceptability of an effect of the data at least in part via a
virtual machine representation of at least a portion of the
hardware of the real machine includes determining whether a network
adapter on, for example, virtual machine 12 has been disabled after
loading at least a portion of the data contained in Link 2.
[1304] The operation 2004 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an operating system of an end user's real machine having
one or more end-user specified preferences. Continuing the example
above, FIG. 1A illustrates the Effect of data acceptability,
determination engine 106. Effect of data acceptability
determination engine 106 may receive data from data retriever
engine 102. FIG. 1A further illustrates the Effect of data
acceptability determination engine 106 further including a virtual
machine module 118 and a user preference database 120. Effect of
data acceptability determination engine 106 may transfer the data
to the virtual machine module 118. Virtual machine module 118 (FIG.
1A) may spawn at least one virtual machine 11, 12, and/or 13, and
transfer the data to at least one of virtual machines 11, 12,
and/or 13. FIG. 1B illustrates virtual machines 11, 12, and 13
encompassing a virtual machine representation of real machine 130,
post (e.g., subsequent to) activation of Link 1, Link 2, and Link
3, respectively (e.g. as at least a part of real machine 130 would
exist had link 1, link 2, and/or link 3 actually been traversed on
real machine 130). FIG. I B illustrates virtual machine 11
including a virtual machine representation of an operating system
(e.g., a state of an operating system and/or network operating
system) of the real machine 130 post activation of Link 1, Examples
of such an operating system might include a computer operating
system (e.g., Microsoft.RTM. Windows 2000, Unix, Linux, etc) and/or
a network operating system (e.g., the Internet Operating System
available from Cisco Technology, Inc. Netware.RTM. available from
Novell, Inc., and/or Solaris available from Sun Microsystems,
Inc.). An example of determining an acceptability of an effect of
the data at least in part via a virtual machine representation
includes determining an acceptability of an effect of the data at
least in part via a virtual machine representation of at least a
portion of an operating system of the real machine include
determining whether a portion of the operating system (e.g.,
Microsoft Vista) on for example, virtual machine 12 has been
disabled after loading at least a portion of the data contained in
Link 2.
[1305] The operation 2006 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least a portion of a computing
device. FIG. 1D illustrates real machine 130 including at least a
part of a computing device 132. The computing device 132 may be any
device capable of processing one or more programming instructions.
For example, the computing device 132 may be a desktop computer, a
laptop computer, a notebook computer, a mobile phone, a personal
digital assistant (PDA), combinations thereof, and/or other
suitable computing devices.
[1306] FIG. 249 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 220 may
include at least one additional operation. Additional operations
may include an operation 2102, and/or an operation 2104.
[1307] The operation 2102 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least one peripheral device.
Continuing the example above, FIG. 1A illustrates the Effect of
data acceptability determination engine 106. Effect of data
acceptability determination engine 106 may receive data from data
retriever engine 102. FIG. 1A further illustrates the Effect of
data acceptability determination engine 106 further including a
virtual machine module 118 and a user preference database 120.
Effect of data acceptability determination engine 106 may transfer
the data to the virtual machine module 118. Virtual machine module
118 (FIG. 1A) may spawn at least one virtual machine 11, 12, and/or
13 that may be a virtual machine representation of at least a part
of real machine 130. Real machine 130 (FIG. 1B) may include at
least one peripheral device. For instance, FIG. 1D illustrates real
machine 130 including at least one peripheral device 134-146. FIG.
1D illustrates a representative view of an implementation of real
machine 130 (e.g., a desktop, notebook, or other type computing
system, and/or one or more peripheral devices) in which all/part of
system 100 may be implemented. FIG. 1D illustrates that
implementations of real machine 130 may include all/part of
computing device 132 and/or all/part of one or one or more
peripherals associated computing device 132.
[1308] The operation 2104 illustrates determining an acceptability
of an effect of the retrieved at least a portion of the data at
least in part via a virtual machine representation of at least a
portion of an end user's real machine having one or more end-user
specified preferences including at least one peripheral device
including at least one peripheral device that is at least one of a
printer, a fax machine, a peripheral memory device, a network
adapter, a music player, a cellular telephone, a data acquisition
device, or a device actuator. Continuing the example above, FIG. 1A
illustrates the Effect of data acceptability determination engine
106. Effect of data acceptability determination engine 106 may
receive data from data retriever engine 102. FIG. 1A further
illustrates the Effect of data acceptability determination engine
106 further including a virtual machine module 118 and a user
preference database 120. Effect of data acceptability determination
engine 106 may transfer the data to the virtual machine module 118.
Virtual machine module 118 (FIG. 1A) may spawn at least one of
virtual machines 11, 12, and/or 13 that may be a virtual machine
representation of at least a part of real machine 130. Real machine
130 may include at least one peripheral device. For instance, FIG.
1D illustrates an end user's real machine may also include at least
a portion of one or more peripheral devices connected/connectable
(e.g., via wired, waveguide, or wireless connections) to real
machine 130. Peripheral devices may include one or more printers
134, one or more fax machines 136, one or more peripheral memory
devices 138 (e.g., flash drive, memory stick), one or more network
adapters 139 (e.g., wired or wireless network adapters), one or
more music players 140, one or more cellular telephones 142, one or
more data acquisition devices 144 (e.g., robots) and/or one or more
device actuators 146 (e.g., a computer-controlled manufacturing
device, medical device, an hydraulic arm, a radiation emitter, or
any other component(s) of industrial/medical systems),
[1309] FIG. 250 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2202, and/or an operation 2204.
[1310] The operation 2202 illustrates providing a data display
option of displaying the retrieved at least a portion of the data.
Continuing the example above, data provider engine 108 (FIG. 1A)
may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying at least a portion of the data. For
instance, data provider engine 108 may receive at least one display
instruction (e.g., OK to display the entire text of link 1) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. Data provider engine 108 may then
display the data. Displayed data may be an unmodified web page of
text, images and/or video, or a web page including links to
additional web pages and may be displayed on an end user's real
machine display such as a computer screen.
[1311] The operation 2204 illustrates providing a data display
option of not displaying the retrieved at least a portion of the
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. I A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of not displaying at least a portion of the data,
For instance, data provider engine 108 may receive at least one do
not display instruction (e.g., Do not display the text of link 1)
from at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 (FIG. 1B) may include one or more
instruction generating modules configured to provide a do not
display instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the do not display instruction to the data provider
engine 108. The data display option of not displaying the data may
include message indicated why the data is not being displayed, or
may be, for example, a blank page displayed on a display of the
real machine.
[1312] FIG. 251 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2302, an operation 2304, and/or an
operation 2306.
[1313] The operation 2302 illustrates providing a data display
option of displaying a modified version of the retrieved at least a
portion of the data. Continuing the example above, data provider
engine 108 (FIG. 1A) may be in communication with Effect of data
acceptability determination engine 106 (FIG. 1A), which may receive
data from data obtainer engine 102 (FIG. 1A). Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of displaying at least a modified
version of the data. For instance, data provider engine 108 (FIG.
1A) may receive at least one modify data instruction (e.g., display
only lines 1-10 of the text of link 1) from at least one component
of Effect of data acceptability determination engine 106 (FIG. 1A).
At least one of virtual machines 11, 12, and/or 13 may include one
or more instruction generating modules configured to provide a
modify data instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the modify data instruction to the data provider
engine 108. The data provider engine 108 may transmit the modify
data instruction to the data modification engine 122 for
modification of the data. Data modification engine may transmit the
modified data to the data provider engine 108. Data provider engine
108 may then display the modified version of the data. Displayed
data may be a modified web page of text, a modified image and/or a
modified video, or a modified web page including links to
additional web pages. For instance, a webpage or website may be
displaying, but any obscenities on the web page or website may
replaced by non-obscene word alternatives.
[1314] The operation 2304 illustrates providing a data display
option of obfuscating an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of data acceptability determination
engine 106 (FIG. 1A), which may receive data from data obtainer
engine 102 (FIG. 1A). Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
to the data provider engine 108 to provide the data display option
of obfuscating (e.g., blurring) a portion of the data (e.g.,
obscene photos). For instance, data provider engine 108 may receive
at least one obfuscate data instruction (e.g., display only
non-obscene portions of the image in link 1) from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A), At least one of virtual machines 11, 12, and/or 13 (FIG.
1B) may include one or more instruction generating modules
configured to provide an obfuscate data instruction to the Effect
of data acceptability determination engine 106 after a comparison
of an activation of a link to a user preference stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the obfuscate data
instruction to the data provider engine 108. The data provider
engine 108 may transmit the obfuscate data instruction to the data
modification engine 122 which may transmit the obfuscate data
instruction to the data obfuscation engine 124. Data obfuscation
engine 124 may transmit the obfuscated data to the data
modification engine 122 for transmission to the data provider
engine 108. Data provider engine 108 may then display the
obfuscated version of the data. For example, obfuscating logic may
obfuscate restricted data or imagery within a webpage or image.
Obfuscation may include blurring or blocking of the objectionable
data portion.
[1315] The operation 2306 illustrates providing a data display
option of anonymizing an objectionable data portion. Continuing the
example above, data provider engine 108 (FIG. 1A) may be in
communication with Effect of data acceptability determination
engine 106 (FIG. 1A), which may receive data from data obtainer
engine 102 (FIG. 1A), Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
and an instruction to the data provider engine 108 to provide the
data display option of anonymizing (e.g., obscuring source
information) for a portion of the data (e.g., graphic videos). For
instance, data provider engine 108 may receive at least one
anonymize data instruction (e.g., obscure source information for
portions of the video in link 1) from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide an
anonymize data instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the anonymize data instruction to the data provider
engine 108. The data provider engine 108 may transmit the anonymize
data instruction to the data modification engine 122 which may
transmit the anonymize data instruction to the data anonymization
engine 126. Data anonymization engine 12.6 may transmit the
anonymized data to the data modification engine 122 for
transmission to the data provider engine 108. Data provider engine
108 may then display the anonymized version of the data. Anonymized
data may be data in which the original identity information of the
data is hidden, obscured, replaced, and/or otherwise modified.
[1316] FIG. 252 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2402, an operation 2404, and/or an
operation 2406.
[1317] The operation 2402 illustrates providing a data display
option of removing, altering, or replacing an objectionable data
portion. Continuing the example above, data provider engine 108
(FIG. 1A) may he in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination and an instruction to the data provider engine 108 to
provide the data display option of removing, altering or replacing
an objectionable data portion (e.g., replacing profanity with
innocuous language) for a portion of the data (e.g., explicit
lyrics). For instance, data provider engine 108 may receive at
least one alter, remove or replace instruction (e.g., obscure
source information for portions of the video in link 1) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide a remove, alter or replace data instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a user preference stored
in a copy of the user preference database 120 (FIG. 1A) spawned on
the virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the remove, alter or
replace data instruction to the data provider engine 108. The data
provider engine 108 may transmit the anonymize data instruction to
the data modification engine 122 which may then remove, alter or
replace the data. Data modification engine 122 may transmit the
data containing removed, altered or replaced portions to the data
provider engine 108. Data provider engine 108 may then display the
data containing removed, altered, or replaced portions. Thus, in
one specific example, a portion of a webpage produced by a search
including data relating to religions other than Catholicism may be
removed from the web page prior to display of the. data on an end
user's real machine display such as a computer screen.
[1318] The operation 2404 illustrates providing a data display
option of displaying a data portion consistent with at least one
setting. Continuing the example above, data provider engine 108
(FIG. 1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data obtainer engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a setting stored, for example, in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If displayed data needs to be
modified to be consistent with at least one setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 (FIG. 1A) may transmit the
modified data to the data provider engine 108. Data provider engine
108 may then display the data consistent with the setting. Thus, a
webpage or website data may be determined to be displayable if the
data satisfies a setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the setting. For instance, a
portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate setting.
[1319] The operation 2406 illustrates providing a data display
option of displaying a data portion consistent with a privacy
related setting. Continuing the example above, at least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an. activation of a link to a privacy related
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, and/or 13. Effect of
data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one
privacy related setting, the data provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data consistent with the privacy related setting. For instance, a
portion of a returned webpage including data requesting private
user information such as a user's social security number or e-mail
address may be removed from the web page prior to display of the
data on a computer screen. Further specific examples include a
webpage or website data may be determined to be displayable if the
data satisfies a setting such as a privacy related setting such as
a setting relating to a user's biographical information or
financial information, a webpage or website data may be determined
to be displayable if the data satisfies a group privacy related
setting such as a work group (e.g., employees of a company), a peer
group (e.g., members of a book club), or a family group (e.g.,
members of family unit) privacy related setting, or a webpage or
website data may be determined to be displayable if the data
satisfies a privacy setting determined by a corporation or other
organization to maintain corporate or organization privacy.
[1320] FIG. 253 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2502.
[1321] The operation 2502 illustrates providing a data display
option of displaying a data portion consistent with a user setting.
Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one user
setting, For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one user setting, the data provider engine
108 (FIG. 1A) may transmit the modify data instruction to the data
modification engine 122 for modification of the data. Data
modification engine 122 (FIG. 1A) may transmit the modified data to
the data provider engine 108. Data provider engine 108 may then
display the data consistent with the user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a user setting when at least one of virtual machines 11,
12, and/or 13 compares the data to the user setting. For instance,
a portion of a webpage produced by a search including non-English
text may be removed from the web page prior to display of the data
on a computer screen. Further, in one specific example, a webpage
or website data may be determined to be displayable if the data
satisfies a peer user setting, or a webpage or website data may be
determined to be displayable if the data satisfies, for instance, a
corporate user setting.
[1322] FIG. 254 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2602.
[1323] The operation 2602 illustrates providing a data display
option of displaying a data portion consistent with a desirability
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If displayed data
needs to be modified to be consistent with at. least one
desirability setting, the data provider engine 108 (FIG. 1A) may
transmit the modify data instruction to the data modification
engine 122 (FIG. 1A) for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data portion consistent with the desirability setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." In other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage or website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[1324] FIG. 255 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2702.
[1325] The operation 2702 illustrates providing a data display
option of displaying a data portion consistent with a workplace
established setting. Continuing the example above, at least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide an instruction
to the Effect of data acceptability determination engine 106 after
a comparison of an activation of a link to a workplace established
setting stored in a copy of the user preference database 120 (FIG.
1A) spawned on the virtual machine 11, 12, and/or 13. Effect of
data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one
workplace established setting, the data provider engine 108 (FIG.
1A) may transmit the modify data instruction to the data
modification engine 122 (FIG. 1A) for modification of the data.
Data modification engine 122 may transmit the modified data to the
data provider engine 108. Data provider engine 108 may then display
the data portion consistent with the workplace established setting.
For instance, the data display option may be displaying on a
display of an end user's real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[1326] FIG. 256 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2802, and/or an operation 2804.
[1327] The operation 2802 illustrates providing a data display
option of displaying a data portion consistent with a safety
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a safety setting stored in
a copy of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If displayed data needs to be
modified to be consistent with at least one safety setting the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data modification engine 122 may transmit
the modified data to the data provider engine 108. Data provider
engine 108 may then display the data portion consistent with the
safety setting. For instance, the data display option may be
displaying on a display of an end user's real machine only a data
portion consistent with child safety setting such as "display only
non-violent data," or "display only ethnic and gender neutral
data."
[1328] The operation 2804 illustrates providing a data display
option Of displaying a data portion consistent with a public safety
setting. Continuing the example above, at least one of virtual
machines 11, 12, and/or 1.3 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a desirability setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If displayed data
needs to be modified to be consistent with at least one public
safety setting, the data provider engine 108 (FIG. 1A) may transmit
the modify data instruction to the data modification engine 122
(FIG. 1A) for modification of the data. Data provider engine 108
may then display the data portion consistent with the public safety
setting. For instance, the data display option may be displaying on
a display of an end user's real machine only a data portion
consistent with public safety setting such as "display only
non-confidential data."
[1329] FIG. 257 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 2902.
[1330] The operation 2902 illustrates providing a data display
option of displaying a data portion consistent with a home safety
setting. Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one home
safety setting. For instance, data provider engine 108 may receive
at least one display instruction from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide an
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a home
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, and/or 13. Effect
of data acceptability determination engine 106 may communicate the
display instruction to the data provider engine 108. If displayed
data needs to be modified to be consistent with at least one home
safety setting, the data provider engine 108 (FIG. 1A) may transmit
the modify data instruction to the data modification engine 122
(FIG. 1A) for modification of the data. Data provider engine 108
may then display the data portion consistent with the home safety
setting, For instance, the data display option may be displaying on
a display of an end user's real machine only a data portion
consistent with home safety setting such as "okay to display
private or confidential data."
[1331] FIG. 258 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3002.
[1332] The operation 3002 illustrates providing a data display
option of displaying a data portion consistent with a workplace
safety setting. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of displaying data consistent with
at least one workplace safety setting. For instance, data provider
engine 108 may receive at least one display instruction from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). Each of virtual machines 11, 12, and/or 13
may include one or more instruction generating modules configured
to provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a workplace safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one workplace safety setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data provider engine 108 may then display
the data portion consistent with the workplace safety setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
workplace safety setting such as "display only non-personal
data."
[1333] FIG. 259 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3102.
[1334] The operation 3102 illustrates providing a data display
option of displaying a data portion consistent with a child safety
setting. Continuing the example above, Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108 to provide the data
display option of displaying data consistent with at least one
child safety setting. For instance, data provider engine 108 may
receive at least one display instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a child safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the display instruction to the data
provider engine 108. If displayed data needs to be modified to be
consistent with at least one child safety setting, the data
provider engine 108 (FIG. 1A) may transmit the modify data
instruction to the data modification engine 122 (FIG. 1A) for
modification of the data. Data provider engine 108 may then display
the data portion consistent with the child safety setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
child safety setting such as "display only non-violent data."
[1335] FIG. 260 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3202, an operation 3204, and/or an
operation 3206.
[1336] The operation 3202 illustrates redirecting to alternative
data. Continuing the example above, data provider engine 108 (FIG.
1A) may be in communication with Effect of data acceptability
determination engine 106 (FIG. 1A), which may receive data from
data retriever engine 102 (FIG. 1A). Effect of data acceptability
determination engine 106 may transfer effect of data acceptability
determination to the data provider engine 108, and an instruction
to provide the data display option of redirecting to alternative
data (e.g., another website). For instance, data provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). Each of virtual machines 11, 12, and/or 13 may include
one or more instruction generating modules configured to provide a
redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a user preference stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect instruction to the data provider
engine 108. The data provider engine 108 may transmit the redirect
data instruction to the data redirection engine 128 for redirection
to alternative data. The data redirection engine 128 may transmit
the redirection to the data provider engine 108. Data provider
engine 108 may then display the alternative data.
[1337] The operation 3204 illustrates automatically redirecting to
alternative data. Continuing the example above, Effect of data
acceptability determination engine 106 may transfer effect of data
acceptability determination to the data provider engine 108 to
provide the data display option of automatically redirecting to
alternative data (e.g., another website) consistent with a user
preference. For instance, data provider engine 108 may receive at
least one automatically redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A), At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an automatically redirect instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate an automatically redirect
to alternative data consistent with the user preference instruction
to the data provider engine 108. The data provider engine 108 may
transmit the redirect instruction to the data redirection engine
128 for automatic redirection to alternative data consistent with
the user preference. The data redirection engine 128 may transmit
the automatic redirection to the data provider engine 108. Data
provider engine 108 may then automatically (e.g., prior to alerting
a user) display the alternative data. For instance, an end user's
real machine 130 may be automatically redirected to an acceptable
web link, or a page of acceptable data.
[1338] The operation 3206 illustrates providing a list of
selectable alternative data options. Continuing the example above,
Effect of data acceptability determination engine 106 may transfer
effect of data acceptability determination to the data provider
engine 108, and an instruction to provide the data display option
of providing a list of selectable alternative data options (e.g., a
list o alternative websites) consistent with a user preference, For
instance, data provider engine 108 may receive at least one provide
selectable alternatives instruction from at least one component of
Effect of data acceptability determination engine 106 (FIG. 1A). At
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to transmit a
provide selectable alternatives instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a user preference stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the provide selectable
alternatives instruction to the data provider engine 108. The data
provider engine 108 may transmit the provide selectable
alternatives instruction to the data redirection engine 128 to
provide selectable alternatives consistent with the user
preference. The data redirection engine 128 may transmit the list
of selectable alternatives to the data provider engine 108, Data
provider engine 108 may then display the list of selectable
alternatives. For instance, the list of selectable alternative data
options may include a list of acceptable web links or a selectable
list of web pages. Selectable web links and web pages may include a
thumbnail image of the first page of the web link or of the web
page.
[1339] FIG. 261 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3302, and/or an operation 3304.
[1340] The operation 3302 illustrates displaying alternative data
consistent with a privacy related setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one privacy
related setting. For instance, data provider engine 108 may receive
at least one display instruction (e.g., OK to display webpage) from
at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide an instruction to the
Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a privacy related setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the display
instruction to the data provider engine 108. If data needs to be
modified to be consistent with at least one privacy related
setting, the data provider engine 108 may transmit the modify data
instruction to the data modification engine 122 for modification of
the data. Data modification engine 122 may transmit the modified
data to the data provider engine 108. Data provider engine 108 may
then display the data consistent with the privacy related setting.
For instance, a portion of a returned webpage including data
requesting private user information such as a user's social
security number or e-mail address may be removed from the web page
prior to display of the data on a computer screen. Further specific
examples include a webpage or website data may be determined to be
displayable if the data satisfies a setting such as a privacy
related setting such as a setting relating to a user's biographical
information or financial information, a webpage or website data may
be determined to be displayable if the data satisfies a group
privacy related setting such as a work group (e.g., employees of a
company), a peer group (e.g., members of a book club), or a family
group (e.g., members of family unit) privacy related setting, or a
webpage or website data may be determined to he displayable if the
data satisfies a privacy setting determined by a corporation or
other organization to maintain corporate or organization
privacy.
[1341] The operation 3304 illustrates displaying alternative data
consistent with a customized user setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one customized
user setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display webpage) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A.). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a customized user setting stored in a copy
of the user preference database 120 (FIG. 1A) spawned on the
virtual machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one customized user setting, the data
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data, Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data consistent with the customized user setting. Thus, a webpage
or website data may be determined to be displayable if the data
satisfies a customized user setting when at least one of virtual
machines 11, 12, and/or 13 compares the data to the customized user
setting. For instance, a portion of a webpage produced by a search
including non-English text may be removed from the web page prior
to display of the data on a computer screen. Further, in one
specific example, a webpage or website data may be determined to be
displayable if the data satisfies a customized peer user setting,
or a webpage or website data may be determined to be displayable if
the data satisfies, for instance, a customized corporate user
setting.
[1342] FIG. 262 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3402.
[1343] The operation 3402 illustrates displaying alternative data
consistent with a desirability setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of displaying data consistent with at least one desirability
setting. For instance, data provider engine 108 may receive at
least one display instruction (e.g., OK to display image) from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A). At least one of virtual machines 11, 12,
and/or 13 may include one or more instruction generating modules
configured to provide an instruction to the Effect of data
acceptability determination engine 106 after a comparison of an
activation of a link to a desirability setting stored in a copy of
the user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one desirability setting, the data
provider engine 108 may transmit the modify data instruction to the
data modification engine 122 for modification of the data. Data
modification engine 122 may transmit the modified data to the data
provider engine 108. Data provider engine 108 may then display the
data portion consistent with the desirability setting. For
instance, the data display option may be displaying on a display of
an end user's real machine only a data portion consistent with a
Christian desirability setting such as "display only Christianity
related data." in other examples, a webpage or website data may be
determined to be displayable if the data satisfies a desirability
setting, a webpage sir website data may be determined to be
displayable if the data satisfies a religious desirability setting
such as a Christian, Jewish, and/or Muslim, based religious
desirability setting, or may be based on any other major, minor or
alternative religious desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
political desirability setting such as a Republican, Democratic,
Libertarian or Green Party political desirability setting, a
webpage or website data may be determined to be displayable if the
data satisfies a cultural desirability setting such as a religious,
ethnic, regional, or heritage based cultural desirability setting
or any other cultural desirability setting, a webpage or website
data may be determined to be displayable if the data satisfies a
theme related desirability setting such as boating or card games,
or a webpage or website data may be determined to be displayable if
the data satisfies an age appropriateness desirability setting such
as a setting based on the Motion Picture of America Association
film rating system.
[1344] FIG. 263 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3502, an operation 3504, and/or an
operation 3506.
[1345] The operation 3502 illustrates displaying alternative data
consistent with a workplace established setting, Continuing the
example above, data provider engine 108 may receive at least one
display instruction (e.g., do not display data) from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide an instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a workplace established setting stored in a copy of the
user preference database 120 (FIG. 1A) spawned on the virtual
machine 11, 12, and/or 13. Effect of data acceptability
determination engine 106 may communicate the display instruction to
the data provider engine 108. If data needs to be modified to be
consistent with at least one workplace established setting, the
data provider engine 108 may transmit the modify data instruction
to the data modification engine 122 for modification of the data.
Data modification engine 122 may transmit the modified data to the
data provider engine 108. Data provider engine 108 may then display
the data portion consistent with the workplace established setting.
For instance, the data display option may be displaying on a
display of an end user's real machine only a data portion
consistent with a workplace appropriateness desirability setting
such as "display only non-obscene data."
[1346] The operation 3504 illustrates displaying alternative data
consistent with a user history setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a user
history setting (e.g., another website). For instance, data
provider engine 108 may receive at least one redirect instruction
from at least one component of Effect of data acceptability
determination engine 106 (FIG. 1A). At least one of virtual
machines 11, 12, and/or 13 may include one or more instruction
generating modules configured to provide a redirect instruction to
the Effect of data acceptability determination engine 106 after a
comparison of an activation of a link to a user history setting
stored in a copy of the user preference database 120 (FIG. 1A)
spawned on the virtual machine 11, 12, and/or 13. Effect of data
acceptability determination engine 106 may communicate the redirect
to alternative data consistent with a user history setting
instruction to the data provider engine 108. The data provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a user history setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data. For
instance, displayed alternative data may be consistent with a user
history such as having viewed only music related data and
pages.
[1347] The operation 3506 illustrates displaying alternative data
consistent with a safety setting. Continuing the example above,
Effect of data acceptability determination engine 106 may transfer
effect of data acceptability determination to the data provider
engine 108, and an instruction to provide the data display option
of redirecting to alternative data consistent with a safety setting
(e.g., another website). For instance, data provider engine 108 may
receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect to alternative data consistent with a
safety setting instruction to the data provider engine 108. The
data provider engine 108 may transmit the redirect data instruction
to the data redirection engine 128 for redirection to alternative
data consistent with a safety setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a safety setting may
include displaying a different webpage including only information
consistent with a safety setting such as "do not display links
requesting credit card information."
[1348] FIG. 264 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3602, and/or an operation 3604.
[1349] The operation 3602 illustrates displaying alternative data
consistent with a workplace safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a
workplace safety setting (e.g., another website). For instance,
data provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a
workplace safety setting stored in a copy of the user preference
database 120 (FIG. 1A) spawned on the virtual machine 11, 12,
and/or 13. Effect of data acceptability determination engine 106
may communicate the redirect to alternative data consistent with a
workplace safety setting instruction to the data provider engine
108. The data provider engine 108 may transmit the redirect data
instruction to the data redirection engine 128 for redirection to
alternative data consistent with a workplace safety setting. The
data redirection engine 128 may transmit the redirection to the
data provider engine 108. Data provider engine 108 may then display
the alternative data. Displaying alternative data consistent with a
workplace safety setting may include displaying a different webpage
including only information consistent with a workplace safety
setting such as "do not display links requesting information on
this computer."
[1350] The operation 3604 illustrates displaying alternative data
consistent with a child safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108 to provide the data display option of
redirecting to alternative data consistent with a child safety
setting (e.g., another website). For instance, data provider engine
108 may receive at least one redirect instruction from at least one
component of Effect of data acceptability determination engine 106
(FIG. 1A). At least one of virtual machines 11, 12, and/or 13 may
include one or more instruction generating modules configured to
provide a redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a child safety setting stored in a copy of the user
preference database 1.20 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a child safety setting instruction to the data
provider engine 108. The data provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a child safety
setting. The data redirection engine 128 may transmit the
redirection to the data provider engine 108. Data provider engine
108 may then display the alternative data. Displaying alternative
data consistent with a child safety setting may include displaying
a different webpage including only information consistent with a
child safety setting such as "do not display links containing
trailers for rated `R.` movies."
[1351] FIG. 265 illustrates alternative embodiments of the example
operational flow 200H of FIG. 230 where the operation 230 may
include at least one additional operation. Additional operations
may include an operation 3702, and/or an operation 3704. The
operation 3702 illustrates displaying alternative data consistent
with a public safety setting. Continuing the example above, at
least one of virtual machines 11, 12, and/or 13 may include one or
more instruction generating modules configured to provide a
redirect instruction to the Effect of data acceptability
determination engine 106 after a comparison of an activation of a
link to a public safety setting stored in a copy of the user
preference database 120 (FIG. 1A) spawned on the virtual machine
11, 12, and/or 13. Effect of data acceptability determination
engine 106 may communicate the redirect to alternative data
consistent with a public safety setting instruction to the data
provider engine 108. The data provider engine 108 may transmit the
redirect data instruction to the data redirection engine 128 for
redirection to alternative data consistent with a public safety
setting. The data redirection engine 128 may transmit the
redirection to the data provider engine 108. Data provider engine
108 may then display the alternative data. Displaying alternative
data consistent with a public safety setting may include displaying
a different webpage including only information consistent with a
public safety setting such as "display only non-confidential data."
Public safety setting may include a transmittable information
safety setting, a viewable information safety setting and a
receivable information safety setting. Transmittable or viewable
information may be private user information, such as credit card
numbers, bank accounts, personal identification information or any
other personal user information. Receivable information may be any
information such as text, images, a virus, spyware, or any other
information that a user's real machine may be capable of receiving
from an external source.
[1352] The operation 3704 illustrates displaying alternative data
consistent with a home safety setting. Continuing the example
above, Effect of data acceptability determination engine 106 may
transfer effect of data acceptability determination to the data
provider engine 108, and an instruction to provide the data display
option of redirecting to alternative data consistent with a public
safety setting (e.g., another website). For instance, data provider
engine 108 may receive at least one redirect instruction from at
least one component of Effect of data acceptability determination
engine 106 (FIG. 1A), Effect of data acceptability determination
engine 106 may transfer effect of data acceptability determination
to the data provider engine 108, and an instruction to provide the
data display option of redirecting to alternative data consistent
with a home safety setting (e.g., another website). For instance,
data provider engine 108 may receive at least one redirect
instruction from at least one component of Effect of data
acceptability determination engine 106 (FIG. 1A). At least one of
virtual machines 11, 12, and/or 13 may include one or more
instruction generating modules configured to provide a redirect
instruction to the Effect of data acceptability determination
engine 106 after a comparison of an activation of a link to a home
safety setting stored in a copy of the user preference database 120
(FIG. 1A) spawned on the virtual machine 11, 12, and/or 13. Effect
of data acceptability determination engine 106 may communicate the
redirect to alternative data consistent with a home safety setting
instruction to the data provider engine 108. The data provider
engine 108 may transmit the redirect data instruction to the data
redirection engine 128 for redirection to alternative data
consistent with a home safety setting. The data redirection engine
128 may transmit the redirection to the data provider engine 108.
Data provider engine 108 may then display the alternative data.
Displaying alternative data consistent with a home safety setting
may include displaying a different webpage including only
information consistent with a home safety setting such as "do not
display links requesting address information."
[1353] Those having skill in the art will recognize that the state
of the art has progressed to the point where there is little
distinction left between hardware, software, and/or firmware
implementations of aspects of systems; the use of hardware,
software, and/or firmware is generally (but not always, in that in
certain contexts the choice between hardware and software can
become significant) a design choice representing cost vs.
efficiency tradeoffs. Those having skill in the art will appreciate
that there are various vehicles by which processes and/or systems
and/or other technologies described herein can be effected (e.g.,
hardware, software, and/or firmware), and that the preferred
vehicle will vary with the context in which the processes and/or
systems and/or other technologies are deployed. For example, if an
implementer determines that speed and accuracy are paramount, the
implementer may opt for a mainly hardware and/or firmware vehicle;
alternatively, if flexibility is paramount, the implementer may opt
for a mainly software implementation; or, yet again alternatively,
the implementer may opt for some combination of hardware, software,
and/or firmware. Hence, there are several possible vehicles by
which the processes and/or devices and/or other technologies
described herein may be effected, none of which is inherently
superior to the other in that any vehicle to be utilized is a
choice dependent upon the context in which the vehicle will be
deployed and the specific concerns (e.g., speed, flexibility, or
predictability) of the implementer, any of which may vary. Those
skilled in the art will recognize that optical aspects of
implementations will typically employ optically-oriented hardware,
software, and or firmware.
[1354] In some implementations described herein, logic and similar
implementations may include software or other control structures
suitable to operation. Electronic circuitry, for example, may
manifest one or more paths of electrical current constructed and
arranged to implement various logic functions as described herein.
In some implementations, one or more media are configured to bear a
device-detectable implementation if such media hold or transmit a
special-purpose device instruction set operable to perform as
described herein. In some variants, for example, this may manifest
as an update or other modification of existing software or
firmware, or of gate arrays or other programmable hardware, such as
by performing a reception of or a transmission of one or more
instructions in relation to one or more operations described
herein. Alternatively or additionally, in some variants, an
implementation may include special-purpose hardware, software,
firmware components, and/or general-purpose components executing or
otherwise invoking special-purpose components. Specifications or
other implementations may be transmitted by one or more instances
of tangible transmission media as described herein, optionally by
packet transmission or otherwise by passing through distributed
media at various times.
[1355] Alternatively or additionally, implementations may include
executing a special-purpose instruction sequence or otherwise
invoking circuitry for enabling, triggering, coordinating,
requesting, or otherwise causing one or more occurrences of any
functional operations described above. In some variants,
operational or other logical descriptions herein may be expressed
directly as source code and compiled or otherwise invoked as an
executable instruction sequence. In some contexts, for example, C++
or other code sequences can be compiled directly or otherwise
implemented in high-level descriptor languages (e.g., a
logic-synthesizable language, a hardware description language, a
hardware design simulation, and/or other such similar mode(s) of
expression). Alternatively or additionally, some or all of the
logical expression may be manifested as a Verilog-type hardware
description or other circuitry model before physical implementation
in hardware, especially for basic operations or timing-critical
applications. Those skilled in the art will recognize how to
obtain, configure, and optimize suitable transmission or
computational elements, material supplies, actuators, or other
common structures in light of these teachings.
[1356] The foregoing detailed description has set forth various
embodiments of the devices and/or processes via the use of block
diagrams, flowcharts, and/or examples. Insofar as such block
diagrams, flowcharts, and/or examples contain one or more functions
and/or operations, it will be understood by those within the art
that each function and/or operation within such block diagrams,
flowcharts, or examples can be implemented, individually and/or
collectively, by a wide range of hardware, software, firmware, or
virtually any combination thereof. In one embodiment, several
portions of the subject matter described herein may be implemented
via Application Specific Integrated Circuits (ASICs), Field
Programmable Gate-Arrays (FPGAs), digital signal processors (DSPs),
or other integrated formats. However, those skilled in the art will
recognize that some aspects of the embodiments disclosed herein, in
whole or in part, can be equivalently implemented in integrated
circuits, as one or more computer programs running on one or more
computers (e.g., as one or more programs running on one or more
computer systems), as one or more programs running on one or more
processors (e.g., as one or more programs running on one or more
microprocessors), as firmware, or as virtually any combination
thereof, and that designing the circuitry and/or writing the code
for the software and or firmware would be well within the skill of
one of skill in the art in light of this disclosure. In addition,
those skilled in the art will appreciate that the mechanisms of the
subject matter described herein are capable of being distributed as
a program product in a variety of forms, and that an illustrative
embodiment of the subject matter described herein applies
regardless of the particular type of signal bearing medium used to
actually carry out the distribution. Examples of a signal bearing
medium include, but are not limited to, the following: a recordable
type medium such as a floppy disk, a hard disk drive, a Compact
Disc (CD), a Digital Video Disk (DVD), a digital tape, a computer
memory, etc.; and a transmission type medium such as a digital
and/or an analog communication medium (e.g., a fiber optic cable, a
waveguide, a wired communications link, a wireless communication
link (e.g., transmitter, receiver, transmission logic, reception
logic, etc.), etc.).
[1357] In a general sense, those skilled in the art will recognize
that the various aspects described herein which can be implemented,
individually and/or collectively, by a wide range of hardware,
software, firmware, and/or any combination thereof can be viewed as
being composed of various types of "electrical circuitry."
Consequently, as used herein "electrical circuitry" includes, but
is not limited to, electrical circuitry having at least one
discrete electrical circuit, electrical circuitry having at least
one integrated circuit, electrical circuitry having at least one
application specific integrated circuit, electrical circuitry
forming a general purpose computing device configured by a computer
program (e.g., a general purpose computer configured by a computer
program which at least partially carries out processes and/or
devices described herein, or--a microprocessor configured by a
computer program which at least partially carries out processes
and/or devices described herein), electrical circuitry forming a
memory device (e.g., forms of memory (e.g., random access, flash,
read only, etc.)), and/or electrical circuitry forming a
communications device (e.g., a modem, communications switch,
optical-electrical equipment, etc.). Those having skill in the art
will recognize that the subject matter described herein may be
implemented in an analog or digital fashion or some combination
thereof.
[1358] Those skilled in the art will recognize that at least a
portion of the devices and/or processes described herein can be
integrated into a data processing system. Those having skill in the
art will recognize that a data processing system generally includes
one or more of a system unit housing, a video display device,
memory such as volatile or non-volatile memory, processors such as
microprocessors or digital signal processors, computational
entities such as operating systems, drivers, graphical user
interfaces, and applications programs, one or more interaction
devices (e.g., a touch pad, a touch screen, an antenna, etc.),
and/or control systems including feedback loops and control motors
(e.g., feedback for sensing position and/or velocity; control
motors for moving and/or adjusting components and/or quantities). A
data processing system may be implemented utilizing suitable
commercially available components, such as those typically found in
data computing/communication and/or network computing/communication
systems.
[1359] The herein described subject matter sometimes illustrates
different components contained within, or connected with, different
other components. It is to be understood that such depicted
architectures are merely exemplary, and that in fact many other
architectures may be implemented which achieve the same
functionality. In a conceptual sense, any arrangement of components
to achieve the same functionality is effectively "associated" such
that the desired functionality is achieved. Hence, any two
components herein combined to achieve a particular functionality
can be seen as "associated with" each other such that the desired
functionality is achieved, irrespective of architectures or
intermedial components. Likewise, any two components so associated
can also be viewed as being "operably connected", or "operably
coupled", to each other to achieve the desired functionality, and
any two components capable of being so associated can also be
viewed as being "operably couplable", to each other to achieve the
desired functionality. Specific examples of operably couplable
include but are not limited to physically mateable and/or
physically interacting components, and/or wirelessly interactable,
and/or wirelessly interacting components, and/or logically
interacting, and/or logically interactable components.
[1360] In some instances, one or more components may be referred to
herein as "configured to," "configurable to," "operable/operative
to," "adapted/adaptable," "able to," "conformable/conformed to,"
etc. Those skilled in the art will recognize that "configured to"
can generally encompass active-state components and/or
inactive-state components and/or standby-state components, unless
context requires otherwise.
[1361] While particular aspects of the present subject matter
described herein have been shown and described, it will be apparent
to those skilled in the art that, based upon the teachings herein,
changes and modifications may be made without departing from the
subject matter described herein and its broader aspects and,
therefore, the appended claims are to encompass within their scope
all such changes and modifications as are within the true spirit
and scope of the subject matter described herein. It will be
understood by those within the art that, in general, terms used
herein, and especially in the appended claims (e.g., bodies of the
appended claims) are generally intended as "open" terms (e.g., the
term "including" should be interpreted as "including but not
limited to," the term "having" should be interpreted as "having at
least," the term "includes" should be interpreted as "includes but
is not limited to," etc.). It will be further understood by those
within the art that if a specific number of an introduced claim
recitation is intended, such an intent will be explicitly recited
in the claim, and in the absence of such recitation no such intent
is present. For example, as an aid to understanding, the following
appended claims may contain usage of the introductory phrases "at
least one" and "one or more" to introduce claim recitations.
However, the use of such phrases should not be construed to imply
that the introduction of a claim recitation by the indefinite
articles "a" or "an" limits any particular claim containing such
introduced claim recitation to claims containing only one such
recitation, even when the same claim includes the introductory
phrases "one or more" or "at least one" and indefinite articles
such as "a" or "an" (e.g., "a" and/or "an" should typically be
interpreted to mean "at least one" or "one or more"); the same
holds true for the use of definite articles used to introduce claim
recitations. In addition, even if a specific number of an
introduced claim recitation is explicitly recited, those skilled in
the art will recognize that such recitation should typically be
interpreted to mean at least the recited number (e.g., the bare
recitation of "two recitations," without other modifiers, typically
means at least two recitations, or two or more recitations).
Furthermore, in those instances where a convention analogous to "at
least one of A, B, and C, etc." is used, in general such a
construction is intended in the sense one having skill in the art
would understand the convention (e.g., "a system having at least
one of A, B, and C" would include but not be limited to systems
that have A alone, B alone, C alone, A and B together, A and C
together, B and C together, and/or A, B, and C together, etc.). In
those instances where a convention analogous to "at least one of A,
B, or C, etc." is used, in general such a construction is intended
in the sense one having skill in the art would understand the
convention (e.g., "a system having at least one of A, B, or C"
would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C
together, and/or A, B, and C together, etc.). It will be further
understood by those within the art that typically a disjunctive
word and/or phrase presenting two or more alternative terms,
whether in the description, claims, or drawings, should be
understood to contemplate the possibilities of including one of the
terms, either of the terms, or both terms. For example, the phrase
"A or B" will be typically understood to include the possibilities
of "A" or "B" or "A and B."
[1362] With respect to the appended claims, those skilled in the
art will appreciate that recited operations therein may generally
be performed in any order. Also, although various operational flows
are presented in a sequence(s), it should be understood that the
various operations may be performed in other orders than those
which are illustrated, or may be performed concurrently. Examples
of such alternate orderings may include overlapping, interleaved,
interrupted, reordered, incremental, preparatory, supplemental,
simultaneous, reverse, or other variant orderings, unless context
dictates otherwise. Furthermore, terms like "responsive to,"
"related to," or other past-tense adjectives are generally not
intended to exclude such variants, unless context dictates
otherwise.
* * * * *
References