U.S. patent application number 13/633557 was filed with the patent office on 2013-02-28 for risk-based model for security policy management.
This patent application is currently assigned to International Business Machines Corporation. The applicant listed for this patent is International Business Machines Corporation. Invention is credited to Christopher Y. Choi, Neil I. Readshaw.
Application Number | 20130055342 13/633557 |
Document ID | / |
Family ID | 47745659 |
Filed Date | 2013-02-28 |
United States Patent
Application |
20130055342 |
Kind Code |
A1 |
Choi; Christopher Y. ; et
al. |
February 28, 2013 |
Risk-based model for security policy management
Abstract
A security policy management solution (such as a Data Loss
Prevention (DLP) system) is augmented to enable a user to model and
visualize how changes in a security policy may impact (positively
or negatively) the effectiveness of a policy configuration as well
as the risk associated with its deployment. This technique enables
a user (e.g., a security policy administrator) to evolve enterprise
information technology (IT) security policies and, in particular,
to generate and display "what-if" scenarios by which the user can
determine trade-offs between, on the one hand, the effectiveness of
a proposed change to a policy, and on the other hand, the risk
associated with the proposed change.
Inventors: |
Choi; Christopher Y.;
(Southport, AU) ; Readshaw; Neil I.; (Parkwood,
AU) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
International Business Machines Corporation; |
Armonk |
NY |
US |
|
|
Assignee: |
International Business Machines
Corporation
Armonk
NY
|
Family ID: |
47745659 |
Appl. No.: |
13/633557 |
Filed: |
October 2, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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13216309 |
Aug 24, 2011 |
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13633557 |
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Current U.S.
Class: |
726/1 |
Current CPC
Class: |
G06F 21/577
20130101 |
Class at
Publication: |
726/1 |
International
Class: |
G06F 21/00 20060101
G06F021/00 |
Claims
1. A method of policy change management, comprising: defining a
version of a policy; quantifying an effectiveness of the policy
version; quantifying a risk associated with the policy version;
mapping, on a machine-implemented graphical display, the
effectiveness and the risk for the policy version; and comparing
the policy version with a prior version of the policy to determine
whether the policy version is to be implemented.
2. The method as described in claim 1 further including mapping, on
the graphical display, the effectiveness and the risk for the prior
version of the policy.
3. The method as described in claim 2 wherein the comparing step is
performed visually, using the graphical display.
4. The method as described in claim 1 wherein the effectiveness is
quantified by assigning a value to an attribute associated with the
policy version.
5. The method as described in claim 4 wherein the attribute
comprises a plurality of effectiveness attributes combined into a
single effectiveness attribute.
6. The method as described in claim 1 wherein the risk is
quantified by assigning a measure of a negative impact of the
policy on an attribute therewith.
7. The method as described in claim 6 wherein the attribute
comprises a plurality of risk attributes combined into a single
risk attribute.
8. The method as described in claim 1 wherein the effectiveness and
the risk for the policy version are mapped in an n-dimensional
space.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Technical Field
[0002] This disclosure relates generally to security policy
management for information technology (IT) systems.
[0003] 2. Background of the Related Art
[0004] Information security is the process of providing a set of
controls to manage risk with an end goal of demonstrating
compliance with a set of regulations. Security policies specify how
a set of controls operate and therefore to what extent risk may be
capable of being managed. The specific values for attributes in a
schema of any security policy can be modified, and such
modifications may change the probability of both positive impact
(effectiveness at managing risk) and negative impact (unhappy
users, loss of productivity) on the environment which the policy is
intended to protect.
[0005] For example, Data Loss Prevention (DLP) systems are
well-known in the prior art and operate generally to identify,
monitor use of, and to control user operations on, sensitive
information within an enterprise computing environment. Typically,
DLP systems provide a policy-based mechanism for managing how data
is discovered and classified on a user's workstation or file
server, also known as an "endpoint." Policies must be distributed
to, and enforced on, each endpoint. A representative DLP policy may
be intended to limit the inappropriate use of sensitive content.
Elements of a DLP policy that change its impact on the organization
include, for example, the set of endpoints/users to which the
policy is applied, the nature of the response when inappropriate
use is detected (e.g. audit the event versus preventing the data
leak by blocking user activity), and the strictness of the
identification of sensitive data (e.g. validation of check sums on
numerical data, number of occurrences, size of training sets,
etc.)
[0006] Information security professionals also are aware of the
concept of risk-based security management. Nevertheless, security
policy management as a technology domain typically does not express
policy explicitly in a way that recognizes the original purpose of
risk management. In this regard, most commercial policy management
systems do not provide policy versioning; moreover, in those
systems that do, policy versions do not link to risk assessment.
This gap is usually caused by the lack of continuity and
consistency from the business view of information security through
to the implementation in IT systems. With increasing emphasis on IT
more directly supporting business objectives, and with IT being
applied to new problem domains (such as smart energy), an overt
representation of the link between security policy and risk is
desired.
[0007] Existing security solutions typically use a predefined set
of security levels and do not allow user-defined versions of
policies to be configured. They also do not provide any mechanism
to enable a user to associate (with a security policy) a risk
assessment determined by an organization. More significantly, such
approaches do not provide any reference to the potential negative
impact of changing security levels.
[0008] There is a need in the art to provide for techniques to
enable those responsible for policy management within an
organization with the ability to link in a quantitative description
of risk.
BRIEF SUMMARY OF THE INVENTION
[0009] The techniques herein augment a security policy management
solution (such as a DLP system) to enable a user to model and
visualize how changes in a security policy may impact (positively
or negatively) the effectiveness of a policy configuration as well
as the risk associated with its deployment. As used herein, a
"policy" may refer to a single policy, or a set of policies. This
technique enables a user (e.g., a security policy administrator) to
evolve information technology (IT) security policies and to
determine trade-offs between, on the one hand, the effectiveness of
a proposed change to a policy, and on the other hand, the risk
associated with the proposed change.
[0010] In one embodiment, a method of policy change management is
implemented in a data processing system. The method begins by a
user defining a version of a policy (e.g., a data loss prevention
policy, an identity provisioning policy, a web access control
policy, and the like), or a set of such policies. The policy
typically has a schema associated therewith, and the schema may
have one or more attributes. A policy schema attribute may be
assigned a value in a given instantiation of a policy. Thus, for
example, in a security policy schema, an attribute may be "number
of users affected," an "enforcement action," or the like. According
to the method, for a given instantiation of a policy, an
"effectiveness" score is then assigned to the policy schema
attribute. This score corresponds to a potential "effectiveness" of
the policy. In addition, and according to the method, a "risk" of
the policy is also quantified, e.g., by assigning a measure of a
potential for negative impact of the policy on a policy schema
attribute. This "risk" is sometimes referred to herein as "policy
risk" or "implementation risk" Once the effectiveness and risk are
quantified, a relationship of the effectiveness and risk associated
with the version of the security policy is then determined.
Preferably, this relationship is plotted in a visual manner,
together with a similar representation for at least one prior
version of the policy. By comparing the plots, the user (e.g., a
security administrator) can readily determine whether and to what
extent the policy should be changed, e.g., by adopting the
user-defined version, by defining a new version, or the like.
[0011] Preferably, the user-defined versions are created using a
menu-based or graphical user interface-based configuration tool.
The resulting display visualizations enable the user to design
security policy changes while evaluating "what-if" scenarios for
the proposed security policy changes.
[0012] In one embodiment, the relationship between effectiveness
and risk of a security policy variant is represented in two
(2)-dimensional space. One or more effectiveness attributes/metrics
may be combined into a single effectiveness metric in that
representation. Likewise, one or more risk attributes/metrics may
be combined into a single risk metric in that representation. In an
alternative embodiment, such relationship data is represented in
n-dimensional space, where each dimension represents an attribute
in the policy schema, and each point in n-dimensional space may
represent a policy instance annotated with its assigned
effectiveness and risk metrics.
[0013] The foregoing has outlined some of the more pertinent
features of the invention. These features should be construed to be
merely illustrative. Many other beneficial results can be attained
by applying the disclosed invention in a different manner or by
modifying the invention as will be described.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] For a more complete understanding of the present invention
and the advantages thereof, reference is now made to the following
descriptions taken in conjunction with the accompanying drawings,
in which:
[0015] FIG. 1 depicts an exemplary block diagram of a distributed
data processing environment in which exemplary aspects of the
illustrative embodiments may be implemented;
[0016] FIG. 2 is an exemplary block diagram of a data processing
system in which exemplary aspects of the illustrative embodiments
may be implemented;
[0017] FIG. 3 illustrates a known data loss prevention (DLP)
solution in which the subject matter of this disclosure may be
implemented;
[0018] FIG. 4 illustrates a process flow illustrating a method for
policy change management according to this disclosure;
[0019] FIG. 5 illustrates a policy configurator tool interface by
which a user defines a policy and associates effectiveness and risk
measures to that policy;
[0020] FIG. 6 illustrates a first visualization according to this
disclosure wherein multiple instances of security policy
configuration are mapped across a two (2)-dimensional space;
[0021] FIG. 7 illustrates a second visualization according to this
disclosure wherein multiple policy dimensions (attributes) that
impact effectiveness and risk are mapped in the space; and
[0022] FIG. 8 illustrates a policy management system in which the
techniques of this disclosure may be implemented.
DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT
[0023] With reference now to the drawings and in particular with
reference to FIGS. 1-2, exemplary diagrams of data processing
environments are provided in which illustrative embodiments of the
disclosure may be implemented. It should be appreciated that FIGS.
1-2 are only exemplary and are not intended to assert or imply any
limitation with regard to the environments in which aspects or
embodiments of the disclosed subject matter may be implemented.
Many modifications to the depicted environments may be made without
departing from the spirit and scope of the present invention.
[0024] With reference now to the drawings, FIG. 1 depicts a
pictorial representation of an exemplary distributed data
processing system in which aspects of the illustrative embodiments
may be implemented. Distributed data processing system 100 may
include a network of computers in which aspects of the illustrative
embodiments may be implemented. The distributed data processing
system 100 contains at least one network 102, which is the medium
used to provide communication links between various devices and
computers connected together within distributed data processing
system 100. The network 102 may include connections, such as wire,
wireless communication links, or fiber optic cables.
[0025] In the depicted example, server 104 and server 106 are
connected to network 102 along with storage unit 108. In addition,
clients 110, 112, and 114 are also connected to network 102. These
clients 110, 112, and 114 may be, for example, personal computers,
network computers, or the like. In the depicted example, server 104
provides data, such as boot files, operating system images, and
applications to the clients 110, 112, and 114. Clients 110, 112,
and 114 are clients to server 104 in the depicted example.
Distributed data processing system 100 may include additional
servers, clients, and other devices not shown.
[0026] In the depicted example, distributed data processing system
100 is the Internet with network 102 representing a worldwide
collection of networks and gateways that use the Transmission
Control Protocol/Internet Protocol (TCP/IP) suite of protocols to
communicate with one another. At the heart of the Internet is a
backbone of high-speed data communication lines between major nodes
or host computers, consisting of thousands of commercial,
governmental, educational and other computer systems that route
data and messages. Of course, the distributed data processing
system 100 may also be implemented to include a number of different
types of networks, such as for example, an intranet, a local area
network (LAN), a wide area network (WAN), or the like. As stated
above, FIG. 1 is intended as an example, not as an architectural
limitation for different embodiments of the disclosed subject
matter, and therefore, the particular elements shown in FIG. 1
should not be considered limiting with regard to the environments
in which the illustrative embodiments of the present invention may
be implemented.
[0027] With reference now to FIG. 2, a block diagram of a data
processing system is shown in which illustrative embodiments may be
implemented. Data processing system 200 is an example of a
computer, such as server 104 or client 110 in FIG. 1, in which
computer-usable program code or instructions implementing the
processes may be located for the illustrative embodiments. In this
illustrative example, data processing system 200 includes
communications fabric 202, which provides communications between
processor unit 204, memory 206, persistent storage 208,
communications unit 210, input/output (I/O) unit 212, and display
214.
[0028] Processor unit 204 serves to execute instructions for
software that may be loaded into memory 206. Processor unit 204 may
be a set of one or more processors or may be a multi-processor
core, depending on the particular implementation. Further,
processor unit 204 may be implemented using one or more
heterogeneous processor systems in which a main processor is
present with secondary processors on a single chip. As another
illustrative example, processor unit 204 may be a symmetric
multi-processor (SMP) system containing multiple processors of the
same type.
[0029] Memory 206 and persistent storage 208 are examples of
storage devices. A storage device is any piece of hardware that is
capable of storing information either on a temporary basis and/or a
permanent basis. Memory 206, in these examples, may be, for
example, a random access memory or any other suitable volatile or
non-volatile storage device. Persistent storage 208 may take
various forms depending on the particular implementation. For
example, persistent storage 208 may contain one or more components
or devices. For example, persistent storage 208 may be a hard
drive, a flash memory, a rewritable optical disk, a rewritable
magnetic tape, or some combination of the above. The media used by
persistent storage 208 also may be removable. For example, a
removable hard drive may be used for persistent storage 208.
[0030] Communications unit 210, in these examples, provides for
communications with other data processing systems or devices. In
these examples, communications unit 210 is a network interface
card. Communications unit 210 may provide communications through
the use of either or both physical and wireless communications
links.
[0031] Input/output unit 212 allows for input and output of data
with other devices that may be connected to data processing system
200. For example, input/output unit 212 may provide a connection
for user input through a keyboard and mouse. Further, input/output
unit 212 may send output to a printer. Display 214 provides a
mechanism to display information to a user.
[0032] Instructions for the operating system and applications or
programs are located on persistent storage 208. These instructions
may be loaded into memory 206 for execution by processor unit 204.
The processes of the different embodiments may be performed by
processor unit 204 using computer implemented instructions, which
may be located in a memory, such as memory 206. These instructions
are referred to as program code, computer-usable program code, or
computer-readable program code that may be read and executed by a
processor in processor unit 204. The program code in the different
embodiments may be embodied on different physical or tangible
computer-readable media, such as memory 206 or persistent storage
208.
[0033] Program code 216 is located in a functional form on
computer-readable media 218 that is selectively removable and may
be loaded onto or transferred to data processing system 200 for
execution by processor unit 204. Program code 216 and
computer-readable media 218 form computer program product 220 in
these examples. In one example, computer-readable media 218 may be
in a tangible form, such as, for example, an optical or magnetic
disc that is inserted or placed into a drive or other device that
is part of persistent storage 208 for transfer onto a storage
device, such as a hard drive that is part of persistent storage
208. In a tangible form, computer-readable media 218 also may take
the form of a persistent storage, such as a hard drive, a thumb
drive, or a flash memory that is connected to data processing
system 200. The tangible form of computer-readable media 218 is
also referred to as computer-recordable storage media. In some
instances, computer-recordable media 218 may not be removable.
[0034] Alternatively, program code 216 may be transferred to data
processing system 200 from computer-readable media 218 through a
communications link to communications unit 210 and/or through a
connection to input/output unit 212. The communications link and/or
the connection may be physical or wireless in the illustrative
examples. The computer-readable media also may take the form of
non-tangible media, such as communications links or wireless
transmissions containing the program code. The different components
illustrated for data processing system 200 are not meant to provide
architectural limitations to the manner in which different
embodiments may be implemented. The different illustrative
embodiments may be implemented in a data processing system
including components in addition to or in place of those
illustrated for data processing system 200. Other components shown
in FIG. 2 can be varied from the illustrative examples shown. As
one example, a storage device in data processing system 200 is any
hardware apparatus that may store data. Memory 206, persistent
storage 208, and computer-readable media 218 are examples of
storage devices in a tangible form.
[0035] In another example, a bus system may be used to implement
communications fabric 202 and may be comprised of one or more
buses, such as a system bus or an input/output bus. Of course, the
bus system may be implemented using any suitable type of
architecture that provides for a transfer of data between different
components or devices attached to the bus system. Additionally, a
communications unit may include one or more devices used to
transmit and receive data, such as a modem or a network adapter.
Further, a memory may be, for example, memory 206 or a cache such
as found in an interface and memory controller hub that may be
present in communications fabric 202.
[0036] Computer program code for carrying out operations of the
present invention may be written in any combination of one or more
programming languages, including an object-oriented programming
language such as Java.TM., Smalltalk, C++ or the like, and
conventional procedural programming languages, such as the "C"
programming language or similar programming languages. The program
code may execute entirely on the user's computer, partly on the
user's computer, as a stand-alone software package, partly on the
user's computer and partly on a remote computer, or entirely on the
remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider).
[0037] Those of ordinary skill in the art will appreciate that the
hardware in FIGS. 1-2 may vary depending on the implementation.
Other internal hardware or peripheral devices, such as flash
memory, equivalent non-volatile memory, or optical disk drives and
the like, may be used in addition to or in place of the hardware
depicted in FIGS. 1-2. Also, the processes of the illustrative
embodiments may be applied to a multiprocessor data processing
system, other than the SMP system mentioned previously, without
departing from the spirit and scope of the disclosed subject
matter.
[0038] As will be seen, the techniques described herein may operate
in conjunction within the standard client-server paradigm such as
illustrated in FIG. 1 in which client machines communicate with an
Internet-accessible Web-based portal executing on a set of one or
more machines. End users operate Internet-connectable devices
(e.g., desktop computers, notebook computers, Internet-enabled
mobile devices, or the like) that are capable of accessing and
interacting with the portal. Typically, each client or server
machine is a data processing system such as illustrated in FIG. 2
comprising hardware and software, and these entities communicate
with one another over a network, such as the Internet, an intranet,
an extranet, a private network, or any other communications medium
or link. A data processing system typically includes one or more
processors, an operating system, one or more applications, and one
or more utilities. The applications on the data processing system
provide native support for Web services including, without
limitation, support for HTTP, SOAP, XML, WSDL, UDDI, and WSFL,
among others. Information regarding SOAP, WSDL, UDDI and WSFL is
available from the World Wide Web Consortium (W3C), which is
responsible for developing and maintaining these standards; further
information regarding HTTP and XML is available from Internet
Engineering Task Force (IETF). Familiarity with these standards is
presumed.
[0039] Although not meant to be limiting, and as described below, a
representative data processing system in which the techniques of
this disclosure are implemented is an appliance-based data loss
prevention (DLP) solution. DLP systems are well-known and work to
reduce the risk of sensitive data loss, primarily at the network
layer. As seen in FIG. 3, a representative DLP solution 300
comprises a set of distributed components, typically arranged in a
tiered architecture. Multiple policy sensors 302 are placed around
the network (typically as rack-based appliances, software
applications, or the like) and are designed to detect and/or
prevent data loss. Generally, in an appliance-based implementation,
an appliance may comprise a data processing system such as
described in FIG. 2. The appliance includes a policy engine that
works generally by capturing packets from the network, reassembling
the packets into sessions, analyzing the information flow,
extracting content for analysis, and performing content analysis to
identify sensitive information. The appliance may use
system-defined or user-defined policies, where a policy represents
a group of one or more rules. A rule typically is a logical
combination of one or more triggers that are content-based,
location-based and/or flow-based. Sessions with policy violations
are detected by the sensors and forwarded a central management
console 304 that distributes policies and collects and organizes
alerts. A data store 306 is used to store data and policies,
typically in a database. The central management console 304
includes a web-based graphical user interface (GUI) for management,
administration and reporting. As used herein, the type of sensitive
information protected by such a DLP solution may be quite varied.
Typically, such information includes, without limitation,
intellectual property (e.g., code, designs, documentation, other
proprietary information), identity information (e.g., personally
identifiable information (PII)), credit card information (such as
PCI-related data), health care information (such as HIPAA-related
data), finance information (such as GLBA-related data), and the
like. As also seen in FIG. 3, the DLP solution is implemented
across one or more endpoints 308. Without limitation, endpoints may
be end user desktops, workstations or laptops, or servers.
[0040] Preferably, a policy is created and managed in the central
management console (such as shown in FIG. 3).
[0041] Thus, in general a DLP system provides a policy-based
mechanism for managing how data is discovered and classified on an
endpoint workstation, file server or other device within an
enterprise. An endpoint is a data processing system (such as
described above in FIG. 2) and that has an associated file system
(or equivalent data store). The endpoint may execute DLP software.
An endpoint typically includes a DLP application that executes as
software, i.e., as a set of program instructions, executed from
computer memory by a processor. The DLP application is configurable
according to a policy, where the policy is created and managed in a
central management console (such as shown in FIG. 3). This is not a
limitation, however, as a particular DLP policy may be implemented
locally (at the endpoint itself).
Risk-Based Model for Security Policy Management
[0042] As described above, the techniques herein augment or enhance
a security policy management solution (including but, without
limitation, a DLP system) to enable a user to model and visualize
how changes in a security policy may impact (positively or
negatively) the effectiveness of a policy configuration as well as
the risk associated with its deployment. As noted above, a "policy"
may refer to a single policy, or a set of policies (a "policy
set"). As will be seen, this technique enables a user, such as a
security policy administrator, to evolve an enterprise information
technology (IT) security policy and, in particular, by determining
trade-offs between an effectiveness of a proposed change to a
policy, and a risk associated with the proposed change.
[0043] In one embodiment, a method of policy change management is
implemented in a data processing system, such as a data processing
system as implemented in FIG. 2. The data processing system may be
connected as a client or a server, such as shown in FIG. 1,
although this is not a limitation, as the techniques described
below may be implemented within a standalone computing system.
[0044] The particular techniques may be used to facilitate
management of any type of policy including, without limitation, a
security policy, an access policy, a data loss prevention policy
(such as in a DLP system), an identity provisioning policy, a web
access control policy, and the like.
[0045] According to the method, an effectiveness versus risk
relationship (or characteristic) for a new version of a policy is
visualized against a similar relationship for one or more prior
versions of the policy. Using this visualization technique, a user
can determine how best to evolve a particular IT policy. By
associating a particular user-defined policy version with an
assessment of risk, and preferably, an organization's own
assessment of such risk, the resulting policy configuration change
can be evaluated and made in a much more intelligent fashion as
compared to the prior art.
[0046] To this end, and as illustrated in FIG. 4, a method of
change management begins at step 400 by a user defining a version
of a policy. As noted above, the policy typically has a schema
associated therewith, and the schema may have one or more
attributes. A policy schema attribute may be assigned a value in a
given instantiation of a policy. Thus, for example, in a security
policy schema, an attribute may be "number of users affected," an
"enforcement action," or the like. Step 400 creates a user-defined
policy. Policy management systems typically include such
functionality, e.g., using software tools and user interface
displays. At step 402, an "effectiveness" of the policy is then
quantified, e.g., by assigning a value to an attribute (or metric)
associated therewith. At step 404, a "risk" of the policy is also
quantified, typically by assigning a measure of a potential for
negative impact of the policy on an attribute (or metric)
associated therewith. Steps 402 and 404 generate values for these
measures. Steps 402 and 404 may be carried out concurrently, or in
reverse order. Once the effectiveness and policy risk are specified
and quantified, the method continues at step 406. At this step, a
relationship of the effectiveness and policy risk associated with
the version of the security policy is then determined. Preferably,
this relationship is then plotted in a visual manner, as indicated
by step 408. At step 410, a similar effectiveness versus risk
representation for at least one prior version of the policy is also
plotted. The representations preferably are plotted on a
computer-implemented display, although this is not a limitation, as
any convenient visual representation may be used. At step 412, and
by comparing the plots, the user determines whether and to what
extent the policy should be changed, e.g., by adopting the
user-defined version, by defining a new version, or the like. This
completes the process.
[0047] Although FIG. 4 describes a single what-if scenario
involving the creation of a single policy version and the
comparison of the version to a single prior version, this is not a
limitation. The same technique can be adapted to provide for
multiple "what-if" scenarios, both sequentially, and concurrently.
The resulting display visualizations (at step 410 and 412) enable
the user to design security policy changes while evaluating
"what-if" scenarios for the proposed security policy changes.
[0048] In addition to enabling "what-if" scenarios to be evaluated,
the technique enables the user to visualize the history of a given
policy or policy set that has been deployed and re-configured in
the past. By being able to visualize multiple policy instances in
this manner, a security administrator also has greater insight into
the "what-if" scenarios that then may be selected for evaluation.
In addition, by having the history, the security administrator may
restore the policy state to a known version if moving to a new
policy version has caused other unintended consequences (i.e., the
negative impact or the risk has been realized).
[0049] Preferably, the user-defined version is created at step 400
using a menu-based or graphical user interface-based configuration
tool. FIG. 5 illustrates a representative policy configuration
interface that may be used for this purpose. In this example, the
policy system implements a data loss prevention (DLP) policy. Thus,
the tool illustrated in FIG. 5 provides a number of fill-in data
fields including, without limitation, a policy name field 502, a
policy description filed 504, a "data to be detected" field 506, a
"groups affected" field 508, and an "enforcement action" field 510.
These field names/tags are not meant to be limiting. Collectively,
the data entered by the user into the upper portion of the
interface 500 creates a "user-defined policy," which is step 400 in
FIG. 4. Of course, one skilled in the art will appreciate that the
scope and content of the data fields will vary depending on the
type of policy being configured. Moreover, other types of GUI
widgets (such as drop-down lists, radio buttons, and the like) may
be used (in lieu of the fill-in fields) to receive the data being
entered.
[0050] As also seen in FIG. 5, and according to this disclosure,
the existing policy management system configuration tool is
extended or augmented to include several additional fill-in fields.
These extensions enable the user to specify and quantify the
"effectiveness" and "risk" measures that have been described above.
In this example, the display panel 500 is extended to include an
"effectiveness" field 512, together with a "risk" field 514. In
this embodiment, the effectiveness field 512 receives a value that
either is numeric, text, or alphanumeric, and that quantifies the
effectiveness of the policy version being defined. Likewise, the
risk field 514 receives a value that either is numeric, text, or
alphanumeric, and that quantifies the risk of the policy version
being defined. Either or both of the effectiveness and risk values
may be user-specified, or system-specified. Typically, an end user
specifies these values manually, but this is not a limitation, as
one or both values may be calculated or derived
programmatically.
[0051] The display tool configurator may be implemented in the
central management console in FIG. 3 or, more generally, in any
data processing system such as shown in FIG. 2. Using the
configurator, a user defines a policy version (which may be an
initial version). The policy version associates "effectiveness"
with "risk," the latter typically being a risk metric that reflects
the administrator's assessment of the risk of implementing the
policy version (or some aspect thereof). The risk metric also may
be a pre-defined or specified risk metric that is received from an
external source or system.
[0052] As used herein, effectiveness typically is a measure of the
extent to which the particular policy configuration being defined
reduces a particular business risk to the organization. In the
context of a DLP system, the business risk is a risk of loss or
theft of sensitive information, or the like. Typically, this
"business risk" is distinct from the policy (or implementation)
risk that has been described above, which for purposes of this
disclosure and as previously defined is a measure of a potential
for negative impact of the policy configuration. A representative
policy risk may be loss of productivity from an overly restrictive
policy. According to this disclosure, and to simplify the
measurement and comparison, a particular policy may be decomposed
into one or more dimensions that impact or influence the
effectiveness and the risk. These dimensions correspond to policy
schema attributes for a given instantiation of the policy. For
example, in one example embodiment, the dimensions (the policy
schema attributes) considered are "enforcement action" and "number
of users affected." These identifiers/tags are merely illustrative,
and they should not be taken as limiting. An example of an
"enforcement action" is an increase in the level of enforcement
from "audit" to "deny" in an authorization or data loss prevention
policy. This change increases the effectiveness of the policy, but
it also increases the risk of adversely impacting the productivity
of the employees. The other dimension, "number of users affected,"
is a metric that is self-defining. Typically, an increase in the
number of users affected by the policy increases the effectiveness
of the policy but also increases the risk that any errors in the
configuration having a wider spread effect.
[0053] According to this disclosure, preferably the configuration
of policies is modeled in one of the several ways. In one approach,
as shown in FIG. 6, multiple instances of security policy
configuration are mapped across a two (2)-dimensional space 600,
with each axis representing one of the effectiveness/risk metrics
mentioned previously. In particular, in this example, the "y" axis
indicates "effectiveness" (and, in particular, effectiveness of the
particular policy for addressing the business risk), while the "x"
axis indicates the potential for negative impact of applying this
particular policy. As shown, each circle in the diagram represents
a specific instance or a specific version of the policy
configuration. Thus, the visualization represents multiple policies
which collectively address a particular security requirement. The
point of origin (x, y)=(0, 0), represents no policy being deployed.
The current policy is represented by circle 602, while a new policy
version is represented by circle 604. As the plot indicates, moving
away from the point of origin, which as noted above represents no
policy being deployed, increases the effectiveness of the policy
configuration as well as the risk associated with its deployment.
The absolute distance from the origin need not be quantified,
because preferably the visualization is used to guide the
progression of the policy configuration based on the relative
measures of risk (as reflected in the plot). For example, in the
plot shown in FIG. 6, the security administrator can immediately
recognize that there are two configurable versions of the policy or
policies: auditing security violations associating with 100 users
(configuration A), and denying violations associated with 1000
users (configuration B). Further, by simply examining the plot, it
is clear that moving from configuration A to configuration B
increases both the effectiveness and the risk. Using this policy
definition and display methodology, a security administrator can
determine a next logical phase of the policy configuration by
examining various tradeoffs between the effectiveness and the risk
associated with a next phase (or subsequent phases).
[0054] An alternative implementation is shown in FIG. 7, which
illustrates a visualization 700 in which multiple policy dimensions
(that impact the effectiveness and the risk) are combined together.
Thus, in this alternative approach, in effect, a number of
effectiveness attributes are combined into a single effectiveness
attribute, while a number of risk attributes are combined into a
single effectiveness attribute. Referring now to the specific
example, as in the previous example (FIG. 6), the policy dimensions
that impact the effectiveness and the risk are identified. As
before, "enforcement action" and "number of users affected" are
utilized for this purpose. For each dimension, the user then
defines levels of increasing effectiveness and risk. For each
level, the effectiveness and risk factors are defined, preferably
using numeric values that are specified by the policy administrator
based on experience, historical data, or some combination. Each
circle in this diagram represents a particular state of the policy,
with circle 702 representing a current state, and circles 704, 706
and 708 representing a particular state of the policy at a future
time (each a policy "version" as has been described). In this
example, the numeric values are merely exemplary and, as noted
above, these values typically are specified by the administrator
(or are otherwise made available to the system). The
effectiveness/risk values are shown. Preferably, just like the
distance values in FIG. 6 did not influence the data, the
effectiveness and risk factors preferably are relative so the
actual numbers do not necessarily matter so long as they are
relative increments to the preceding levels. As can be seen, and as
represented by the circles 704, 706 and 708, in this example
different versions of policy configuration are configured at
specific points in the space depicted. In particular, each circle
in the diagram represents a specific policy configuration. One such
configuration (i.e., circle 702) represents auditing violations
across 100 users. In the example, this configuration has a
perceived effectiveness of "3" and risk of "3," which is an
aggregate of the risk metrics along all represented dimensions. The
policy configuration is "changed" in effect by moving along one or
more dimensions. As can be seen, as the position of the effective
policy changes, the total risk and the effectiveness factor are
displayed. Using this visualization, the security administrator can
simulate the policy change to determine the relative risk before
committing the policy change.
[0055] The visualizations shown in FIG. 6 and FIG. 7 may be
provided by a display interface, such as a graphical user interface
(GUI) operating in a data processing system.
[0056] The particular techniques for authoring different instances
of policy configuration and ranking them based on their risk
metrics (effectiveness and risk) may utilize known methodologies
(and are outside the scope of this disclosure). Of course, if an
organization is risk-adverse and prefers a phased approach, then
more time should be invested in determining the dimensions of the
policy that impacts the risk. This allows more fine-grained
evolution of the policy configuration, as it enables the
configuration to be changed in smaller increments along only one of
the dimensions. If, on the other hand, the organization is
time-constrained to meet a specific set of compliance requirements,
then coarse-grained levels may be needed and a simpler model (such
as shown in the example in FIG. 7) is preferred. In some cases,
certain dimensions of a policy will be of lower risk for certain
organizations. For example, for an organization that uses a small
set of roles, it might be relatively low risk to apply the policies
to a larger number of users because the policies are still being
applied to the same types of users. In this case, moving the policy
configuration along the "number of users affect" dimension
represents a lower risk compared to moving the configuration along
the "enforcement action" dimension. Preferably, the visualization
tool is configurable to represent the difference in relative
magnitude.
[0057] Although FIG. 6 and FIG. 7 illustrate just two policy
dimensions to simplify the visualization, this is not a limitation.
The techniques described herein may be implemented with higher
dimensions (n-dimensional space).
[0058] FIG. 8 illustrates a representative policy management system
800 in which the above-described technique may be implemented. The
system 800 may be implemented across one or more machines operating
in a computing environment, such as shown in FIG. 1. Typically, the
system comprises a policy administration point (PAP) 802, a policy
decision point (PDP) 804, and a policy enforcement point (PEP) 806.
Generally, the policy administration point 802 is used to define a
policy, which may be specified as a set of XACML policy
expressions. This policy uses subject attributes provided from a
user repository 808, as well runtime and environment data received
from policy information point (PIP) 810. The policy decision point
(PDP) 804 receives similar information and responds to an XACML
policy query received from the policy enforcement point (PEP) 806
to enforce the policy on a subject and with respect to a particular
action initiated by the subject. In one commercial implementation
of this approach, the PAP 802 is implemented by IBM.RTM.
Tivoli.RTM. Security Policy Manager (TSPM) policy service/console,
the PDP 804 is implemented in the TSPM runtime security service,
and the PEP is implemented as a TSPM plug-in to WebSphere.RTM.
Application Server. In this embodiment, which is merely
illustrative, the policy definition and visualization technique is
implemented within the policy administration point.
[0059] The visualization may be implemented with any convenient
visualization tool. Representative tools for this purpose include
an user interface (UI) toolkit, whether web-based or thick
client-based. Examples include, without limitation, Eclipse
plug-ins, Dojo JavaScript widgets, Adobe.RTM. Flash, Microsoft.RTM.
.NET controls, and the like.
[0060] The subject matter described herein has many advantages. The
technique provides for more explicit linkage between business and
technical views of security policy in an organization. It enables
better and more efficient planning for the evolution of a
particular security policy (or policies) throughout a rollout of an
IT system with security controls. Further, it enables the
relationship between security policy and risk to be an integrated
artifact of an IT system, as opposed to separate
considerations.
[0061] The visualization technique described herein enables the
quantifying of the negative impact of applying a security policy or
a plurality of security policies. As such, the described technique
recognizes and addresses the practical and operational limitations
of a security policy management system. The technique
advantageously provides the user with insight into the net
effectiveness of a security policy, preferably by incorporating the
operational risk (i.e., the negative impact) of employing that
policy, not merely the benefits thereof (which can also be
visualized, as described). The described technique has the further
advantage in that it provides a way of modeling or representing the
natural progression of enterprise-wide security policies and
associated effectiveness, as well as the risk associated with each
phase of that progression. The subject disclosure facilitates
predictive modeling and visual representation of policy data so
that the operational risk of employing a particular policy can be
seen.
[0062] The functionality described above may be implemented as a
standalone approach, e.g., a software-based function executed by a
processor, or it may be available as a managed service (including
as a web service via a SOAP/XML interface). The particular hardware
and software implementation details described herein are merely for
illustrative purposes are not meant to limit the scope of the
described subject matter.
[0063] More generally, computing devices within the context of the
disclosed invention are each a data processing system (such as
shown in FIG. 2) comprising hardware and software, and these
entities communicate with one another over a network, such as the
Internet, an intranet, an extranet, a private network, or any other
communications medium or link. The applications on the data
processing system provide native support for Web and other known
services and protocols including, without limitation, support for
HTTP, FTP, SMTP, SOAP, XML, WSDL, UDDI, and WSFL, among others.
Information regarding SOAP, WSDL, UDDI and WSFL is available from
the World Wide Web Consortium (W3C), which is responsible for
developing and maintaining these standards; further information
regarding HTTP, FTP, SMTP and XML is available from Internet
Engineering Task Force (IETF). Familiarity with these known
standards and protocols is presumed.
[0064] The scheme described herein may be implemented in or in
conjunction with various server-side architectures including simple
n-tier architectures, web portals, federated systems, and the like.
The techniques herein may be practiced in a loosely-coupled server
(including a "cloud"-based) environment.
[0065] Still more generally, the subject matter described herein
can take the form of an entirely hardware embodiment, an entirely
software embodiment or an embodiment containing both hardware and
software elements. In a preferred embodiment, the function is
implemented in software, which includes but is not limited to
firmware, resident software, microcode, and the like. Furthermore,
as noted above, the DLP policy association functionality described
herein can take the form of a computer program product accessible
from a computer-usable or computer-readable medium providing
program code for use by or in connection with a computer or any
instruction execution system. For the purposes of this description,
a computer-usable or computer readable medium can be any apparatus
that can contain or store the program for use by or in connection
with the instruction execution system, apparatus, or device. The
medium can be an electronic, magnetic, optical, electromagnetic,
infrared, or a semiconductor system (or apparatus or device).
Examples of a computer-readable medium include a semiconductor or
solid state memory, magnetic tape, a removable computer diskette, a
random access memory (RAM), a read-only memory (ROM), a rigid
magnetic disk and an optical disk. Current examples of optical
disks include compact disk-read only memory (CD-ROM), compact
disk-read/write (CD-R/W) and DVD. The computer-readable medium is a
tangible item.
[0066] The computer program product may be a product having program
instructions (or program code) to implement one or more of the
described functions. Those instructions or code may be stored in a
computer readable storage medium in a data processing system after
being downloaded over a network from a remote data processing
system. Or, those instructions or code may be stored in a computer
readable storage medium in a server data processing system and
adapted to be downloaded over a network to a remote data processing
system for use in a computer readable storage medium within the
remote system.
[0067] In a representative embodiment, the policy definition and
visualizations described above are implemented in a special purpose
computer, preferably in software executed by one or more
processors. The software is maintained in one or more data stores
or memories associated with the one or more processors, and the
software may be implemented as one or more computer programs.
Collectively, this special-purpose hardware and software comprises
or supplements an existing policy management solution, as has been
described
[0068] In a representative embodiment, a policy management central
management console (e.g., a DLP central management console) exposes
one or more web-based interfaces that may be used to create and/or
modify a policy, and/or to visualize the policy effectiveness/risk
relationships in the manner described.
[0069] As noted, the described functionality may be implemented as
an adjunct or extension to an existing policy management
solution.
[0070] While the above describes a particular order of operations
performed by certain embodiments of the invention, it should be
understood that such order is exemplary, as alternative embodiments
may perform the operations in a different order, combine certain
operations, overlap certain operations, or the like. References in
the specification to a given embodiment indicate that the
embodiment described may include a particular feature, structure,
or characteristic, but every embodiment may not necessarily include
the particular feature, structure, or characteristic.
[0071] Finally, while given components of the system have been
described separately, one of ordinary skill will appreciate that
some of the functions may be combined or shared in given
instructions, program sequences, code portions, and the like.
[0072] Any application or functionality described herein may be
implemented as native code, by providing hooks into another
application, by facilitating use of the mechanism as a plug-in, by
linking to the mechanism, and the like.
[0073] The techniques disclosed herein are not limited to a
middleware policy management appliance (such as a DLP appliance)
that monitors network traffic such as has been described, but this
will be a typical implementation. As noted, the above-described
identity-centric policy association function may be used in any
system, device, portal, site, or the like wherein it is desired to
analyze data for inclusion of sensitive information.
[0074] As used herein, the term "quantifying," as it relates to an
"effectiveness" measure or a "risk" measure, refers to generating
such a measure, or receiving the measure as generated by another
person, entity or automated system.
[0075] Having described our invention, what we now claim is as
follows.
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