U.S. patent application number 14/311253 was filed with the patent office on 2014-10-09 for systems and methods for managing data incidents.
The applicant listed for this patent is Identity Theft Guard Solutions, LLC. Invention is credited to Greg L. Kotka, Susan M. Rook, Mahmood Sher-Jan.
Application Number | 20140304822 14/311253 |
Document ID | / |
Family ID | 48946786 |
Filed Date | 2014-10-09 |
United States Patent
Application |
20140304822 |
Kind Code |
A1 |
Sher-Jan; Mahmood ; et
al. |
October 9, 2014 |
Systems and Methods for Managing Data Incidents
Abstract
Systems and methods for managing a data incident are provided
herein. Exemplary methods may include receiving data breach data
that comprises information corresponding to the data breach,
automatically generating a risk assessment from a comparison of
data breach data to privacy rules, the privacy rules comprising at
least one federal rule and at least one state rule, each of the
rules defining requirements associated with data breach
notification laws, and providing the risk assessment to a display
device that selectively couples with the risk assessment
server.
Inventors: |
Sher-Jan; Mahmood; (Lake
Oswego, OR) ; Rook; Susan M.; (Beaverton, OR)
; Kotka; Greg L.; (Vancouver, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Identity Theft Guard Solutions, LLC |
Portland |
OR |
US |
|
|
Family ID: |
48946786 |
Appl. No.: |
14/311253 |
Filed: |
June 21, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13691661 |
Nov 30, 2012 |
8763133 |
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14311253 |
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13396558 |
Feb 14, 2012 |
8707445 |
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13691661 |
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Current U.S.
Class: |
726/25 |
Current CPC
Class: |
H04L 63/1416 20130101;
H04L 63/1408 20130101; G06F 21/6245 20130101; G06F 21/577 20130101;
H04L 63/08 20130101; G06F 21/60 20130101; G06F 21/00 20130101; H04L
63/1433 20130101 |
Class at
Publication: |
726/25 |
International
Class: |
H04L 29/06 20060101
H04L029/06 |
Claims
1. A method for managing a data incident, comprising: receiving,
via a risk assessment server, data incident data that comprises
information corresponding to the data incident; and automatically
generating, via the risk assessment server, a risk assessment from
a comparison of the data incident data to privacy rules, the
privacy rules comprising at least one federal rule and at least one
state rule, each of the rules defining requirements associated with
data incident notification laws.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is a continuation of U.S.
Non-Provisional patent application Ser. No. 13/691,661 filed on
Nov. 30, 2012 titled "Systems and Methods for Managing Data
Incidents", which is a continuation of U.S. Non-Provisional patent
application Ser. No. 13/396,558 filed on Feb. 14, 2012 titled
"Systems and Methods for Managing Data Incidents", which are hereby
incorporated by reference.
FIELD OF THE TECHNOLOGY
[0002] Embodiments of the disclosure relate to information privacy.
More specifically, but not by way of limitation, the present
technology relates to the management of data incidents. The
management of a data incident may comprise conducting an analysis
of a data incident data relative to federal and state privacy rules
and generating a risk assessment and incident response plan for the
data incident. Additionally, the present technology may generate
notification schedules and gather/transmit notification information
for data incidents having a risk assessment that is indicative of a
high level of risk.
BACKGROUND OF THE DISCLOSURE
[0003] Data incidents involve the exposure of sensitive information
such as personally identifiable information and protected health
information to third parties. Data incidents may comprise data
breaches, privacy breaches, privacy or security incidents, and
other similar events that result in the exposure of sensitive
information to third parties. Some of these exposures may be
subject to numerous state and federal statutes that delineate
requirements that are to be imposed upon the party that was
entrusted to protect the data. Personally identifiable information
(hereinafter "PII") and protected health information (PHI) which,
regards healthcare related information for individuals that are
maintained by a covered entity (e.g., an entity that has been
entrusted with the PHI such as a hospital, clinic, health plan, and
so forth), may include, but is not limited to, healthcare,
financial, political, criminal justice, biological, location,
and/or ethnicity information. For purposes of brevity, although
each of these types of PII and PHI may have distinct nomenclature,
all of the aforementioned types information will be referred to
herein as PII/PHI.
SUMMARY OF THE DISCLOSURE
[0004] According to some embodiments, the present technology may be
directed to methods managing a data incident. The methods may
comprise: (a) receiving, via a risk assessment server, data
incident data that comprises information corresponding to the data
incident; (b) automatically generating, via the risk assessment
server, a risk assessment from a comparison of data incident data
to privacy rules, the privacy rules comprising at least one federal
rule and at least one state rule, each of the rules defining
requirements associated with data incident notification laws; and
(c) providing, via the risk assessment server, the risk assessment
to a display device that selectively couples with the risk
assessment server.
[0005] According to other embodiments, the present technology is
directed to a risk assessment server for managing a data incident.
In some instances, risk assessment server may comprise: (a) a
memory for storing executable instructions; (b) a processor for
executing the instructions; (c) an input module stored in memory
and executable by the processor to receive data incident data, the
data incident data comprising information corresponding to the data
incident; (d) a risk assessment generator stored in memory and
executable by the processor to generate a risk assessment from a
comparison of the data incident data to privacy rules, the privacy
rules comprising at least one federal rule and at least one state
rule, each of the rules defining requirements associated with data
incident notification laws; and (e) a notification module stored in
memory and executable by the processor to provide the risk
assessment to a display device that selectively couples with the
risk assessment server.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] The accompanying drawings, where like reference numerals
refer to identical or functionally similar elements throughout the
separate views, together with the detailed description below, are
incorporated in and form part of the specification, and serve to
further illustrate embodiments of concepts that include the claimed
disclosure, and explain various principles and advantages of those
embodiments.
[0007] The methods and systems disclosed herein have been
represented where appropriate by conventional symbols in the
drawings, showing only those specific details that are pertinent to
understanding the embodiments of the present disclosure so as not
to obscure the disclosure with details that will be readily
apparent to those of ordinary skill in the art having the benefit
of the description herein.
[0008] FIG. 1 illustrates an exemplary system for practicing
aspects of the present technology;
[0009] FIG. 2 illustrates an exemplary conversion application for
managing data incidents;
[0010] FIG. 3 illustrates an exemplary GUI in the form of a data
incident details page;
[0011] FIG. 4 illustrates an exemplary GUI in the form of a data
incident dashboard;
[0012] FIG. 5 illustrates an exemplary GUI in the form of a state
specific risk assessment selection and notification page;
[0013] FIG. 6 illustrates an exemplary GUI in the form of a data
sensitivity level evaluation and selected federal and state
specific risk assessments page;
[0014] FIG. 7 illustrates an exemplary GUI in the form of a federal
risk assessment page;
[0015] FIG. 8 illustrates an exemplary GUI in the form of a state
specific risk assessment page;
[0016] FIG. 9 illustrates an exemplary GUI in the form of a statute
summary page;
[0017] FIG. 10 illustrates an exemplary GUI in the form of an
aggregated notification schedules page;
[0018] FIGS. 11-13 illustrate exemplary GUIS that are utilized to
collect, store, and transmit pertinent documents or data;
[0019] FIG. 14 is a flowchart of an exemplary method for managing a
data incident; and
[0020] FIG. 15 illustrates an exemplary computing device that may
be used to implement embodiments according to the present
technology.
DETAILED DESCRIPTION
[0021] In the following description, for purposes of explanation,
numerous specific details are set forth in order to provide a
thorough understanding of the disclosure. It will be apparent,
however, to one skilled in the art, that the disclosure may be
practiced without these specific details. In other instances,
structures and devices are shown at block diagram form only in
order to avoid obscuring the disclosure.
[0022] Generally speaking, the present technology may be directed
to managing data incidents. It will be understood that the terms
"data incident" may be understood to encompass privacy incidents,
security incidents, privacy breaches, data breaches, data leaks,
information breaches, data spills, or other similarly related
events related to the intentional or unintentional release of
protected information to an untrusted environment. This protected
information may be referred to as personally identifiable
information (hereinafter "PII/PHI") or protected health information
(e.g., an entity that has been entrusted with the PHI such as a
hospital, clinic, health plan, and so forth).
[0023] PII/PHI may encompass a wide variety of information types,
but non-limiting examples of PII comprise an individual's full
name, a date of birth, a birthplace, genetic information, biometric
information (face, finger, handwriting, etc.), national
identification number (e.g., social security), vehicle registration
information, driver's license numbers, credit card numbers, digital
identities, and Internet Protocol addresses.
[0024] Other types of information may, in some instances, be
categorized as PII/PHI, such as an individual's first or last name
(separately), age, residence information (city, state, county,
etc.), gender, ethnicity, employment (salary, employer, job
description, etc.), and criminal records--just to name a few. It is
noteworthy to mention that the types of information that are
regarded as PII are subject to change and therefore may include
more or fewer types of information that those listed above.
Additionally, what constitutes PII/PHI may be specifically defined
by a local, state, federal, or international data privacy laws.
[0025] While entities that are subject to these privacy laws may be
referred to in a variety of ways, for consistency and clarity an
entity (either individual or corporate) that is entrusted with
PII/PHI will hereinafter be referred to as an "entrusted
entity."
[0026] It will be understood that the privacy laws contemplated
herein may comprise details regarding not only how an entrusted
entity determines if a data incident violates the law, but also
when the provision of notification to one or more privacy agencies
and/or the customers of the entrusted entity is warranted.
[0027] According to some embodiments, the present technology is
directed to generating risk assessments for data incidents. These
risk assessments provides specific information to the entrusted
entity regarding the severity of the data incident relative to a
state or federal rule. Additionally, the risk assessment provides
information regarding the data sensitivity for the data incident.
That is, the risk assessment may determine if the type of data that
was exposed is highly sensitive information. As mentioned before,
some PII/PHI may be considered more sensitive than others. For
example, a social security number may be more sensitive than a
gender description, although the relative sensitivity for different
categories of PII/PHI are typically delineated in the privacy rules
and may require delineation in the context of each data
incident.
[0028] The present technology may determine the severity and/or
data sensitivity for a data incident by collecting data incident
data from an entrusted entity. This data incident data may be
compared against one or more selected privacy rules to determine
the severity and/or data sensitivity for the data incident. In some
instances, the present technology may model the data incident data
to the one or more privacy rules.
[0029] According to some embodiments, the privacy rules described
herein may comprise the content of a state and/or federal statute.
In other embodiments, the privacy rules may comprise abstracted or
mathematically expressed rules that have been generated from the
text of the state and/or federal statute. Applying a privacy rule
to the data incident data may yield values for the severity and/or
the data sensitivity of the data incident.
[0030] In some embodiments, the risk assessment may provide
indication to the entrusted entity that an obligation has occurred.
More specifically, if the severity of the data incident and/or the
data sensitivity of the data incident when compared to the privacy
rules indicates that the data incident has violated at least one of
the privacy rules, the risk assessment may include an indication
that an obligation has been created. An obligation may require the
entrusted entity to notify subjected individuals that their PII/PHI
has been potentially exposed. The obligation may also require that
notification be provided to a regulating authority such as the
department of Health and Human Services (HHS), Office for Civil
Rights (OCR), Federal Trade Commission, a state agency, or any
agency that regulates data incident notification.
[0031] The present technology allows entrusted entities to model
data incident data to privacy rules which include at least one
state rule and at least one federal rule. In some instances,
entrusted entities may model data incidents to the rules of several
states to generate risk assessments of each of the states. This is
particularly helpful when entrusted entities service customers in
many states. Moreover, each of these states may have differing
notification requirements, along with different metrics for
determining when a data incident requires notification.
[0032] In some embodiments, the risk assessment may include a risk
level that is associated with a color. More specifically, a hue of
the color is associated with the severity of the data incident as
determined by the comparison or modeling if the data incident
data.
[0033] According to the present disclosure, the present technology
may generate a notification schedule for an entrusted entity along
with mechanisms that aid the entrusted entity in gathering
pertinent information that is to be provided to the customer and/or
one or more regulator agencies.
[0034] These and other advantages of the present technology will be
described in greater detail with reference to the collective FIGS.
1-15.
[0035] FIG. 1 illustrates an exemplary system 100 for practicing
aspects of the present technology. The system 100 may include a
risk assessment system, hereinafter "system 105" that may be
implemented in a cloud-based computing environment, or as a web
server that is particularly purposed to manage data incidents.
[0036] In general, a cloud-based computing environment is a
resource that typically combines the computational power of a large
grouping of processors and/or that combines the storage capacity of
a large grouping of computer memories or storage devices. For
example, systems that provide a cloud resource may be utilized
exclusively by their owners; or such systems may be accessible to
outside users who deploy applications within the computing
infrastructure to obtain the benefit of large computational or
storage resources.
[0037] The cloud may be formed, for example, by a network of web
servers, with each web server (or at least a plurality thereof)
providing processor and/or storage resources. These servers may
manage workloads provided by multiple users (e.g., cloud resource
customers or other users). Typically, each user places workload
demands upon the cloud that vary in real-time, sometimes
dramatically. The nature and extent of these variations typically
depend on the type of business associated with the user.
[0038] In other embodiments, the system 105 may include a
distributed group of computing devices such as web servers that do
not share computing resources or workload. Additionally, the system
105 may include a single computing device, such as a web server,
that has been provisioned with one or more programs that are
utilized to manage data incidents.
[0039] End users may access and interact with the system 105 via
the client device 110 through a web-based interface, as will be
discussed in greater detail infra. Alternatively, end users may
access and interact with the system 105 via a downloadable program
that executes on the client device 110. The system 105 may
selectively and communicatively couple with a client device 110 via
a network connection 115. The network connection 115 may include
any one of a number of private and public communications mediums
such as the Internet.
[0040] Additionally, the system 105 may collect and transmit
pertinent information to regulatory agencies, such as regulatory
agency 120, as will be discussed in greater detail infra. In some
instances, notification may also be provided to affected
individuals 125.
[0041] The system 105 may be generally described as a mechanism for
managing data incidents. The system 105 may manage a data incident
by collecting data incident data for the data incident and then
modeling the data incident data to privacy rules. As mentioned
previously, the privacy rules may include at least one state rule
and at least one federal rule. The modeling of the data incident
data may be utilized to generate a risk assessment for the data
incident. The risk assessment may be utilized by an entrusted
entity to determine how best to respond to the data incident. The
system 105 is provided with a risk assessment application 200 that
will be described in greater detail with reference to FIG. 2.
[0042] FIG. 2 illustrates a risk assessment application,
hereinafter referred to as application 200. In accordance with the
present disclosure, the application 200 may generally include a
user interface module 205, an input module 210, a risk assessment
generator 215, a notification module 220, and a reporting module
225. It is noteworthy that the application 200 may include
additional modules, engines, or components, and still fall within
the scope of the present technology. Moreover, the functionalities
of two or more modules, engines, generators, or other components
may be combined into a single component.
[0043] As used herein, the terms "module," "generator," and
"engine" may also refer to any of an application-specific
integrated circuit ("ASIC"), an electronic circuit, a processor
(shared, dedicated, or group) that executes one or more software or
firmware programs, a combinational logic circuit, and/or other
suitable components that provide the described functionality. In
other embodiments, individual modules of the application 200 may
include separately configured web servers. Also, the application
200 may be provisioned with a cloud.
[0044] Generally described, the application 200 allows entrusted
entities to input data incident data, have one or more risk
assessments generated, and receive the one or more risk
assessments, along with notifications schedules, as required.
[0045] An entrusted entity may interact with the application 200
via a graphical user interface that is provisioned as a web-based
interface. The web-based interface may be generated by the user
interface module 205. It will be understood that the user interface
module 205 may generate a plurality of different graphical user
interfaces that allow individuals associated with the entrusted
entity (e.g., privacy officer, compliance officer, security
officer, attorney, employee, agent, etc.) to utilize interact with
the application 200. Examples of graphical user interfaces that are
generated by the user interface module 205 are provided in FIGS.
3-13, which will be described in greater detail infra.
[0046] Upon the occurrence of a data incident, the input module 210
may be executed to receive data incident data from the entrusted
entity. It is noteworthy that the user interface module 205 may
generate different types of graphical user interfaces that are
tailored to obtain specific types of data incident data from the
entrusted entity.
[0047] Initially, it may be desirous for the entrusted entity to
establish a profile that may be utilized to determine if the entity
that is using the application 200 is, in fact, an entrusted entity.
It is noteworthy that to mention that the determination of what
entities are entrusted entities depends upon the privacy rule. For
example, an entity may be considered to be an entrusted entity
under a particular federal statute, but may not be labeled an
entrusted entity under one or more state statutes. Likewise,
different states may have discrepant methods for determining who
constitutes an entrusted entity.
[0048] Therefore, it may be advantageous to determine information
about the entity such as what types of information they collect and
where they conduct business. The input module 210 may be executed
to solicit pertinent information from the entity that may be
utilized to determine if the entity is an entrusted entity. Again,
the entity may specify a plurality of states in which they conduct
business, or the states of residence/domicile for customers with
which they conduct business.
[0049] If it is determined that the entity is an entrusted entity,
the input module may further solicit data incident data for one or
more data incidents. Pertinent data incident data may include the
type of data that was compromised, the date of compromise, the
amount of data that was compromised, were there security measures
in place (e.g., encryption, redaction, etc.), was the incident
intentional or unintentional, was the incident malicious or
non-malicious, how the data was compromised (e.g., theft of laptop,
database security failure, lost storage media, hacked application,
hacked computing device (e.g., web server, email server, content
repository, etc.), and other types of information that assist in
determining a risk level for the data incident as well as any
notification obligations.
[0050] In some instances, rather than soliciting generalized data
incident data from the entrusted entity, the input module 210 may
select questions that solicit data that is particularly relevant to
the privacy rules to which the entrusted entity is subject. For
example, if a privacy rule specifies that a threshold amount of
records must be exposed in order to create an obligation, the end
user may be asked if their amount of exposed records meets or
exceeds that threshold amount. This type of tailored questioning
narrows the analysis that is performed of the data incident data
and improves the efficiency of the risk assessment process.
[0051] Once the data privacy data has been received, the input
module 210 may generate a summary of the data privacy data (or at
least a portion of the data) that is provided to the entrusted
entity via a graphical user interface generated by the user
interface module 205.
[0052] The input module 210 may be configured to solicit
confirmation from the entrusted entity that the data privacy data
in the summary is correct. If the data is incorrect, the entrusted
entity may go back and correct the errant data.
[0053] As mentioned briefly above, the input module 210 may solicit
and receive one or more selections of one or more states from the
entrusted entity. Using the selections, the input module 210 may
select one or more state statutes based upon the one or more
selections. Also, the input module 210 may generate at least one
state rule for each selected state statute. Additionally, one or
more federal rules may be selected and generated as well.
[0054] The input module 210 may generate a state or federal privacy
rule by evaluating the state/federal statute and creating a
plurality of qualifications from the statutes. Qualifications for a
statute may include, for example, thresholds or formulas that are
used to determine if the data incident data of a data incident
violates the statute. Stated otherwise, these qualifications may be
used as a mathematical model of a statute. Data incident data may
be evaluated in light of the model. The resultant modeling may be
used to generate a risk assessment for the data incident.
[0055] The risk assessment generator 215 may be executed to
generate one or more risk assessments for the data incident. The
risk assessment generator 215 may model the data incident data to
the selected or determined privacy rules to determine if an
obligation has been triggered under a privacy rule.
[0056] Again, risk assessments may be generated by modeling the
data incident data to at least one state rule and at least one
federal rule. The risk assessment may combine risk levels for each
rule into a single risk assessment, or individual risk assessments
may be generated for each rule.
[0057] Modeling of the data incident data to a privacy rule (either
state or federal) by the risk assessment generator 215 may result
in the generation of a severity value and a data sensitivity value
for the data incident. The severity value may represent the extent
to which PII/PHI has been compromised, while the data sensitivity
value may represent the relative sensitivity of the PII/PHI that
was compromised. These two factors may independently or dependently
serve as the basis for determining if a notification obligation
exists. For example, if the severity value meets or exceeds a
threshold amount, a notification obligation may exist. If the data
sensitivity value meets or exceeds a threshold amount, a
notification obligation may exist. In some instance, a notification
obligation may only exist if the sensitivity value and the data
sensitivity value both exceed threshold amounts. Again, the
threshold amounts are specified by the particular privacy rule that
is being applied to the data incident data.
[0058] The risk assessment generator 215 may also determine and
apply exceptions that exist in a state or federal statute during
the generation of a risk assessment. These exceptions may be noted
and included in the risk assessment.
[0059] The risk assessment generator 215 may create a visual
indicator such as a risk level or heat map that assists the
entrusted entity in determining if a data incident is relatively
severe or is relatively benign. This visual indicator may be
included in the risk assessment. For example, a risk assessment may
include a risk level that includes a visual indicator such as a
colored object. In some embodiments, a hue of the object is
associated with the severity of the data incident where red may
indicate a severe risk and green may indicate a benign risk, with
orange or yellow hues falling somewhere therebetween. Examples of
heat maps and risk levels indicators are illustrated in FIG. 7.
[0060] Included in the risk assessment, in some instances, is a
summary of sections of the state or federal privacy statute. For
example, with regard to a state specific assessment, the risk
assessment generator 215 may generate an outline of key information
about the state statute that was utilized to generate the state
specific risk assessment. This outline may be displayed to the
entrusted entity via a user interface.
[0061] If the risk assessment generator 215 determines that the
data incident violates one or more statutes (e.g., high severity
value, PII/PHI is very sensitive, etc.), the notification module
220 may be executed to generate a notification schedule. The
notification schedule may be generated based upon a data associated
with the data incident. That is, the statute may specify when
notification is to occur, relative to the date that PII was
exposed.
[0062] Additionally, the notification schedule informs the
entrusted entity as to what types of information are to be
provided, along with the regulatory bodies to which the information
should be provided. Again, the notification schedule may be
generated from the statute itself. For example, a statute may
specify that the data incident data (or a portion of the data
incident data) collected by the input module 210 should be provided
to a particular state agency within a predetermined period of time.
Again, if a plurality of states have been designated or selected,
the notification schedule may include notification dates for each
state agency.
[0063] To assist the entrusted entity in meeting their notification
obligations, the reporting module 225 may be executed to gather
pertinent documents or other information from the entrusted entity
and transmit these documents to the required reporting authorities.
The reporting module 225 may prompt the entrusted entity to attach
documents via a user interface. Once attached, these documents/data
may be stored in a secured repository for submission to regulatory
agency. In other instances, the entrusted entity may transmit
required information directly to the regulatory agency.
[0064] Additionally, the reporting module 225 may provide required
notifications to affected individuals, such as the individuals
associated with the PII/PHI that was compromised.
[0065] FIGS. 3-13 illustrate various exemplary graphical user
interfaces (GUI) that are generated by the user interface module
205. Each of the exemplary user interfaces will be described
below.
[0066] FIG. 3 illustrates an exemplary GUI in the form of a data
incident summary page. The summary page 300 includes a plurality of
received answers to questions that were provided to the entrusted
entity. Responses that were received indicate that the data
incident involved the loss of a cellular telephone, an incident
date of Jan. 2, 2012, an incident discover date of Jan. 16, 2012,
and other pertinent data incident data.
[0067] FIG. 4 illustrates an exemplary GUI in the form of a data
incident dashboard page 400. The page 400 includes listing of
pending and completed risk assessments for a plurality of data
incidents. Each entry may include a risk indicator having a
particular color to help the entrusted entity in quickly
determining data incidents that are high risk. A risk indicator may
be associated with a particular privacy rule. For example, a risk
indicator for an Employee Snooping data incident indicates that a
moderately high risk is associated with the data incident relative
to HITECH rules (e.g., rules associated with the compromise of
PHI). This moderately high risk is indicated by a yellow dot placed
within a row of a "HITECH Status" column. Additionally, a severe
risk is associated with a state privacy rule. This severe risk is
indicated by a red dot placed within a row of a "State Impact"
column.
[0068] FIG. 5 illustrates an exemplary GUI in the form of a state
specific selection and notification page 500. The notification page
is shown as comprising an image that informs the trusted entity
that six states have been affected by the data incident. To view a
risk assessment for each state, the trusted entity may click on any
of the stated listed in the leftmost frame.
[0069] FIG. 6 illustrates an exemplary GUI in the form of a data
sensitivity level evaluation page 600. The page includes a
plurality of data sensitivity indicators the sensitivity for
different types of PII/PHI that were compromised by the data
incident. For example, medical record numbers are shown in red as
being highly sensitive. Moreover, medical record numbers may pose
financial, reputational, and medical harm, which are just some of
the dimensions of potential harm caused by compromise of PII/PHI.
In contrast, the data incident also compromised individual's date
of birth. As determined by entrusted entity, that type of PII/PHI
is not considered highly sensitive and thus, has been depicted in
green.
[0070] FIG. 7 illustrates an exemplary GUI in the form of a risk
assessment page 700. The risk assessment page 700 includes a heat
map 705 and corresponding risk level indicator 715, which is placed
within the heat map 705. The heat map 710 includes a grid where
vertical placement indicates data sensitivity level and horizontal
placement indicates severity level. As is shown, as the sensitivity
and severity levels increase, so do the odds that the data incident
may trigger an obligation to notify affected parties. In this
instance, the risk level is high because the sensitivity level is
high and the severity level is extreme.
[0071] Positioned below the heat map 705 is a notification schedule
that includes not only the obligations for the entrusted entity,
but also the expected notification dates. Again, this schedule may
be based upon requirements included in the violated statute.
[0072] FIG. 8 illustrates an exemplary GUI in the form of a state
specific risk assessment page 800. The page 800 includes a risk
assessment for the State of California. The state impact is shown
as high and a summary of the types of PII/PHI that were exposed are
summarized below the state impact indicator. Similarly to the risk
assessment page 700 of FIG. 7, a notification schedule is included
on the state specific risk assessment page 800. It is noteworthy
that a state specific risk assessment page may be generated for
each affected state (such as the affected states listed on the
state specific selection and notification page 500 of FIG. 5.
[0073] FIG. 9 illustrates an exemplary GUI in the form of a statute
summary page 900. The statute summary page 900 includes a copy (or
a portion) of the privacy statutes (California Civil Code 1798.29
& 1798.82; California Health and Safety Code 1280.15) that were
utilized to generate the state specific risk assessment that was
provided on in FIG. 8. Note that the summary also includes whether
the state statutes include harm test and exceptions which are
flagged by the risk assessment generator 215 according to the
specific privacy statutes.
[0074] FIG. 10 illustrates an exemplary GUI in the form of an
aggregated notification page 1000. The page 1000 includes a
notification schedule for each affected privacy statues (e.g.,
federal and state(s)) relative to one or more data incidents. A
list of notification events is provided and the end user may
utilize the check boxes to select which states (or federal) risk
assessment notification schedules are displayed.
[0075] FIGS. 11-13 illustrate exemplary GUIS that are utilized to
collect, store, and transmit pertinent documents or data. FIG. 11
illustrates an attachments page 1100 that shows a plurality of
documents that have been uploaded to the system such as media
notification, attorney general notification, privacy policy, and
corrective action plan. Positioned adjacent to the list of
documents is a checklist that includes all the pertinent
documentation that is to be provided to regulatory authorities, the
media, and/or affected individuals. As the required data are
uploaded, each required data category is noted with a green check
mark. Missing elements can be easily determined and uploaded.
[0076] It is noteworthy to mention that the on-time reporting of
required incident data may be paramount in determining compliance
and good faith on the part of an entrusted entity. Consequently,
failure to meet required notification deadlines may result in fines
and other regulatory punishment.
[0077] FIG. 12 illustrates an upload page 1200 that may be utilized
by an entrusted entity to upload and categorize required compliance
information (e.g., documents shown in FIG. 11). Files may be tagged
with metadata linking them to the related federal and states risk
assessments before they are stored in a content repository or
transmitted to an appropriate party.
[0078] FIG. 13 illustrates an exemplary time stamped notation and
actions page 1300 that displays notes entered into the system by a
particular end user. Actions may include a note that a particular
employee is to be retrained and certified. Any type of related
action such as a remedial action, uploading of a file, or other
notification and/or compliance related action may be noted and
associated with a particular risk assessment.
[0079] FIG. 14 illustrates a flowchart of an exemplary method for
managing a data incident. The method may include a step 1405 of
receiving data incident data. The data incident data may include
information that pertains or corresponds to the data incident.
Also, the method may include a step 1410 of automatically
generating a risk assessment from a comparison of data incident
data to privacy rules. The privacy rules may comprise at least one
federal rule and at least one state rule, where each of the rules
defining requirements associated with data incident notification
laws. Additionally, the comparison may include modeling the data
incident data against privacy rules. Also, the method may include a
step 1415 of providing the risk assessment to a display device that
selectively couples with a risk assessment server. It is noteworthy
to mention that the risk assessment may include a visual
representation of the risk associated with a data incident relative
to the privacy rules.
[0080] Additionally, for data incidents that violate a privacy rule
(either state or federal) the method may include a step 1420 of
generating a notification schedule for the data incident, along
with an optional step 1425 of transmitting notification information
to a regulatory agency and/or affected individuals (e.g. those
who's PII/PHI has been compromised).
[0081] FIG. 15 illustrates an exemplary computing device 1500 that
may be used to implement an embodiment of the present technology.
The computing device 1500 of FIG. 15 (or portions thereof) may be
implemented in the context of system 105 (FIG. 1). The computing
device 1500 of FIG. 15 includes one or more processors 1510 and
main memory 1520. Main memory 1520 stores, in part, instructions
and data for execution by processor 1510. Main memory 1520 may
store the executable code when in operation. The system 1500 of
FIG. 15 further includes a mass storage device 1530, portable
storage medium drive(s) 1540, output devices 1550, user input
devices 1560, a graphics display 1570, and peripheral devices
1580.
[0082] The components shown in FIG. 15 are depicted as being
connected via a single bus 1590. The components may be connected
through one or more data transport means. Processor unit 1510 and
main memory 1520 may be connected via a local microprocessor bus,
and the mass storage device 1530, peripheral device(s) 1580,
portable storage device 1540, and display system 1570 may be
connected via one or more input/output (I/O) buses.
[0083] Mass storage device 1530, which may be implemented with a
magnetic disk drive or an optical disk drive, is a non-volatile
storage device for storing data and instructions for use by
processor unit 1510. Mass storage device 1530 may store the system
software for implementing embodiments of the present invention for
purposes of loading that software into main memory 1520.
[0084] Portable storage device 1540 operates in conjunction with a
portable non-volatile storage medium, such as a floppy disk,
compact disk, digital video disc, or USB storage device, to input
and output data and code to and from the computing device 1500 of
FIG. 15. The system software for implementing embodiments of the
present invention may be stored on such a portable medium and input
to the computer device 1500 via the portable storage device
1540.
[0085] Input devices 1560 provide a portion of a user interface.
Input devices 1560 may include an alphanumeric keypad, such as a
keyboard, for inputting alpha-numeric and other information, or a
pointing device, such as a mouse, a trackball, stylus, or cursor
direction keys. Additionally, the computing device 1500 as shown in
FIG. 15 includes output devices 1550. Suitable output devices
include speakers, printers, network interfaces, and monitors.
[0086] Display system 1570 may include a liquid crystal display
(LCD) or other suitable display device. Display system 1570
receives textual and graphical information, and processes the
information for output to the display device.
[0087] Peripherals 1580 may include any type of computer support
device to add additional functionality to the computer system.
Peripheral device(s) 1580 may include a modem or a router.
[0088] The components provided in the computing device 1500 of FIG.
15 are those typically found in computer systems that may be
suitable for use with embodiments of the present invention and are
intended to represent a broad category of such computer components
that are well known in the art. Thus, the computing device 1500 of
FIG. 15 may be a personal computer, hand held computing device,
telephone, mobile computing device, workstation, server,
minicomputer, mainframe computer, or any other computing device.
The computer may also include different bus configurations,
networked platforms, multi-processor platforms, etc. Various
operating systems may be used including Unix, Linux, Windows,
Macintosh OS, Palm OS, Android, iPhone OS and other suitable
operating systems. The computing device 1500 may also utilize web
browser applications that display the web-based graphical user
interfaces described herein. Exemplary web browser applications may
include, but are not limited to, Internet Explorer, Firefox,
Safari, Chrome, and other web browser applications that would be
known to one of ordinary skill in the art with the present
disclosure before them. Moreover, when the computing device 1500 is
a mobile computing device, the computing device 1500 may likewise
include mobile web browser applications.
[0089] It is noteworthy that any hardware platform suitable for
performing the processing described herein is suitable for use with
the technology. Computer-readable storage media refer to any medium
or media that participate in providing instructions to a central
processing unit (CPU), a processor, a microcontroller, or the like.
Such media may take forms including, but not limited to,
non-volatile and volatile media such as optical or magnetic disks
and dynamic memory, respectively. Common forms of computer-readable
storage media include a floppy disk, a flexible disk, a hard disk,
magnetic tape, any other magnetic storage medium, a CD-ROM disk,
digital video disk (DVD), any other optical storage medium, RAM,
PROM, EPROM, a FLASHEPROM, any other memory chip or cartridge.
[0090] While various embodiments have been described above, it
should be understood that they have been presented by way of
example only, and not limitation. The descriptions are not intended
to limit the scope of the technology to the particular forms set
forth herein. Thus, the breadth and scope of a preferred embodiment
should not be limited by any of the above-described exemplary
embodiments. It should be understood that the above description is
illustrative and not restrictive. To the contrary, the present
descriptions are intended to cover such alternatives,
modifications, and equivalents as may be included within the spirit
and scope of the technology as defined by the appended claims and
otherwise appreciated by one of ordinary skill in the art. The
scope of the technology should, therefore, be determined not with
reference to the above description, but instead should be
determined with reference to the appended claims along with their
full scope of equivalents.
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