Controlling access to sensitive data based on changes in information classification

A Data Loss Prevention (DLP) system includes an automated method for tracking changes to a security classification (e.g., content category) associated with an artifact to determine whether an attempt is being made to subvert a DLP policy. The method exploits the basic principle that, depending on context, the classification of a particular artifact, or a change to an existing classification, may indicate an attempt to subvert the policy. According to the method, an artifact classification state machine is implemented within a DLP system. For each policy-defined content category on each artifact, the machine identifies a content category change that may be of interest, as defined by policy. When a change in a classification has occurred, an artifact notification event (or, more generally, a notification of the change in classification) is issued.

BACKGROUND OF THE INVENTION

1. Technical Field

This disclosure relates generally to identifying and managing user operations with respect to sensitive information (e.g., intellectual property, personally identifiable information, and the like).

2. Background of the Related Art

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. DLP systems are designed to prevent data flow from inside the network to the outside world. This data flow may be unintentional or intentional. Unlike event-based notification systems, DLP provides a policy-based approach for managing how data is discovered and classified on a user's workstation or file server, also known as an “endpoint.” In such systems, data of interest (sometimes referred to as an “artifact,” an “item” or an “object”) is classified into various well-defined “content categories,” such as “company confidential” or “personally identifiable information (PII).” Additionally, an artifact may be categorized into none, one, or multiple categories. Understanding of the various categories of documents (or other files of interest) that exist on computer systems within an organization helps to inform authorized personnel having a need to access and manage sensitive data. DLP technologies address the problem of data loss by enforcing policy on artifacts and, in particular, by preventing or auditing actions (such as copying a file to external storage) on artifacts based on content category.

Even with a DLP system in place, users will undoubtedly attempt to subvert the technology, e.g., by attempting to modify a classification for given information. The prior art, however, does not provide any automated techniques for determining (and potentially acting upon) changes in information classification. This subject matter of this disclosure addresses this deficiency.

BRIEF SUMMARY OF THE INVENTION

A Data Loss Prevention (DLP) system includes an automated method for tracking changes to a security classification (e.g., content category) associated with an artifact to determine whether an attempt is being made to subvert a DLP policy. The method exploits the basic principle that, depending on context, the classification of a particular artifact, or a change to an existing classification, may indicate an attempt to subvert the policy. According to the method, an artifact classification state machine is implemented within a DLP system. For each policy-defined content category on each artifact, the machine identifies a content category change that may be of interest, as defined by policy. When a change in a classification has occurred, an artifact notification event (or, more generally, a notification of the change in classification) is issued. Thus, for example, a classification event is triggered when an artifact that is previously unknown to the system is first classified. A declassification event is triggered when an artifact is declassified, i.e., when it is no longer classified within a particular content category. A classification rate event is triggered when there is a significant relative increase in a particular content category on a system. The artifact notification events are then examined so that authorized personnel or systems can make decisions about the validity of the user actions reported by the events.

In one embodiment, a method detects changes to artifact classifications in a system that provides data loss prevention (DLP), wherein a DLP policy identifies one or more classifications. The method preferably is carried out in an automated manner, for each policy-defined classification (e.g., content category) on each of a plurality of artifacts. For a particular artifact, the method begins by classifying content of the artifact into a classification identified in the policy. Then, using a state machine, a determination is made whether a change in the classification of the artifact has occurred. If so, a notification of the change in classification is then generated and may be provided to a DLP server for further action.

In an alternative embodiment, the above-described method is performed in a DLP apparatus. The apparatus comprises a processor, and computer memory that holds computer program instructions executed by the processor to carry out the information classification change detection method.

In another alternative embodiment, the above-described method is performed by a computer program product in a computer readable medium for use in a DLP system. The computer program product holds computer program instructions which, when executed by the data processing system, perform the method.

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.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

As will be seen, the techniques described herein may operate in conjunction within the standard client-server paradigm such as illustrated inFIG. 1in 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 inFIG. 2comprising 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.

Although not meant to be limiting, 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 inFIG. 3, a representative DLP solution300comprises a set of distributed components, typically arranged in a tiered architecture. Multiple policy sensors302are 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 inFIG. 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 console304that distributes policies and collects and organizes alerts. A data store306is used to store data and policies, typically in a database. The central management console304includes 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 inFIG. 3, the DLP solution is implemented across one or more endpoints308.

Preferably, a policy is created and managed in the central management console (such as shown inFIG. 3).

DLP functionality may also be built into other enterprise systems, such as an intrusion detection system (IDS), an intrusion protection system (IPS), network firewalls, web gateways, mail servers or relays, enterprise content management systems, or the like. Thus, for example, an IPS can monitor and detect attack traffic, and DLP support can be added to perform outbound DLP protection and associated blocking of the transfer of sensitive content.

Thus, in general a DLP system in which the subject matter herein is implemented 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. As used herein, in general an endpoint is a data processing system (such as described above inFIG. 2) and that has an associated file system (or equivalent data store). The endpoint may execute DLP software. As noted, a representative endpoint is a data processing system that 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 inFIG. 3). This is not a limitation, however, as a particular DLP policy may be implemented locally (at the endpoint itself).

A DLP policy governs access to artifacts of interest in the system. A policy includes information relating to the classifications of the artifacts. The subject matter of this disclosure assumes that the artifacts are already classified or are being classified with particular classifications, sometimes referred to as “security” classifications.

FIG. 4illustrates an information classification change detection mechanism400according to this disclosure. As illustrated, the mechanism400is positioned between a DLP server402and an artifact data store404. Typically, the mechanism is implemented on a DLP client that comprises a set of programs or processes (and associated data) executing on an “endpoint” (e.g., a user's workstation, a file server, or the like), although this is not a limitation. A DLP server402is known in the prior art and comprises a set of programs or processes (and associated data) used to define and manage a DLP policy against artifacts that are available in the data store404. The data store404may be local, remote, centralized, or distributed. As has been described, a DLP policy includes content categories (such as “Company Confidential, Personally Identifiable Information, or the like), including (in the context of this disclosure) at least one such content category that is “of interest,” i.e., that will be examined for content category changes by the technique described below. According to this disclosure, a DLP policy is extended to also include an artifact number threshold, below which artifacts matching content categories of interest do not generate an event. These attributes may be set through a management console GUI, by programmatic methods, or other known techniques.

The mechanism400comprises a set of functional components or modules. Preferably, these components include a change detector406that provides the detection function, a policy management component408, a classifier component410, and an event engine412. The mechanism400also includes or has associated therewith a classification data store414. The classification data store414may store artifact state information for a particular artifact. These components of the detection mechanism400may be integral with one another, or they may be distinct functional components as illustrated. One or more of the components may run in different machines, execution environments or networks. One or more of the components may run as a managed service. One or more components may comprise functions or components of an existing DLP system, such as a known DLP client executing on an endpoint, or a known DLP server. One of ordinary skill will appreciate that the configuration of the mechanism may be varied. Typically, the components illustrated inFIG. 4are implemented in software, as a set of program instructions, executed by one or more processors.

In operation, at step (1) the DLP server402sends a policy to the policy management component408. As noted above, the policy includes content categories, including at least one such category of interest. At step (2), the classifier component410reads the contents of an artifact and classifies it into a content category as specified in the policy that has been sent to the policy management component. At step (3), and with respect to the artifact, the classifier component410notifies the change detector406of an artifact identifier (ID), content category and a “match flag.” A match flag is true if the artifact matches the specified content category. The match flag is false (not true) if the artifact does not match the specified content category. At step (4), the change detector406implements a state machine, as will be described below with respect toFIG. 5, using the policy supplied by the policy management component408and artifact state information (if present) as retrieved from the classification data store414. By examining artifact state transitions, the state machine determines content category changes for a given artifact. Based on these transitions (and the information in the policy), at step (5), the change detector notifies the event engine412. At step (6), the event engine412constructs and issues an artifact notification event, and sends that event to the DLP server402. There are different “types” of notification events, as will be described below. Events that arrive at the DLP server402preferably are examined, e.g., using reporting tools, to facilitate the highlighting of particular events of interest. Authorized personnel can then make decisions about the validity of the user actions reported by the events.

Referring now toFIG. 5, an artifact classification state diagram is shown. This diagram depicts a set of artifact states and various transitions that may be of interest. The change detector406inFIG. 4implements this artifact state machine to determine whether content category changes have occurred for a given artifact. Preferably, the diagram shown inFIG. 5applies for each known content category for a given artifact.

The state diagram500preferably includes the following states: unknown502, unclassified504, declassified506, and classified508. The “unknown” state502refers to the situation wherein no attempt has been made to classify the artifact. There is no record of the artifact in the DLP system. The unclassified state504is one in which artifact classification has been attempted, but there is no match for the given content category. The declassified state506is one in which artifact classification has been attempted but there is no match for the given content category. The declassified state is for artifacts that were previously categorized in the given content category but no longer match. A policy typically defines how long the artifact should remain in the declassified state. The policy may also define other policy decisions on the artifact to more closely monitor attempted user actions while in the declassified state. As will be described, a transition into this state results in a declassification event being sent to the DLP server. The classified state508is one in which artifact classification has been attempted and the given content category matched.

The state diagram500identifies a number of transitions, which are now described. In all case, a new state is recorded in the classification data store414as the artifact state information. As will be seen, with one exception, all state transitions are the result of a classification attempt on the artifact.

State transition (1) in the diagram identifies a transition from the unknown state502to the unclassified state504. No event is generated for this transition, and there is no match for content category.

State transition (2) in the diagram identifies a transition from the unknown state502to the classified state508. This transition generates a standard artifact classification event. In addition, if content category is of interest (according to the policy), and a number of classifications (as defined in the policy or elsewhere) is greater than a threshold (also as defined in the policy or elsewhere), this transition generates a classification rate event.

State transition (3) in the diagram identifies a transition from the unclassified state504to the classified state508. This transition also generates a standard artifact classification event. As a user generates artifacts, this transition is expected.

State transition (4) in the diagram identifies a transition from the classified state508to the declassified state506. This transition generates an artifact declassification event.

State transition (5) in the diagram identifies a transition from the declassified state506to the classified state508. This transition also generates a standard artifact classification event.

State transition (6) in the diagram identifies a transition from the declassified state506to the unclassified state504. Preferably, a policy defines when and under what circumstances to transition to the unclassified state504occurs. Thus, for example, the policy may indicate that transition (6) is only permitted after a predetermined amount of time, upon a number of classification attempts, upon a manual intervention, or the like. The policy also preferably defines what actions to perform (e.g., event generation) as a result of this particular transition.

The above-described nomenclature for the notification events is merely representative. In addition, the state transitions described are representative but provide for a robust set of artifact state classifications and their associated transitions that are implemented by the artifact state machine. Other transition states may be included and used to generate appropriate notifications. As has been described, the artifact state machine implements content category changes for a given artifact, and the state transitions preferably apply for each known content category for an artifact.

The subject matter described herein has many advantages. The technique provides an automated mechanism for tracking the changes to the classification of an artifact, such as a file, an email, a data object, or the like. In a typical operation, if the security classification of a particular artifact changes from one content category to another, then that shift may be used as a flag to alert a supervisor (or an automated system) of an attempt to subvert a policy rule. Additionally, those changes may trigger changes to policy to detect potentially undesirable user behavior and to prevent undesirable user actions. For example, if a document had been categorized as “Company Confidential” and later found (by the artifact state machine) to no longer be categorized as such, such a change could allow the owner to subvert an enforcement policy that otherwise denies copying of the document to a USB memory stick. Additionally, if a large number of objects of a particular category appear on a system, that action may also cause a flag to be raised with appropriate personnel. Once category changes have been detected, authorized personnel can be alerted to suspicious changes, preferably via an event mechanism. In particular, and as described above, preferably a declassification event is triggered when an artifact is declassified, i.e., when it is no longer classified within a particular content category. A classification rate event is triggered when there is a given relative increase in a particular content category on a system.

The detection mechanism typically does not affect whether an operation on an item (e.g., a content change) is or is not carried out by a user. Thus, in a typical case, declassification itself does not prevent access to the object, although subsequent attempts to access the item may be disallowed or authorized personnel notified. By providing such notification, the DLP policy can be adapted as necessary.

The detection mechanism advantageously notifies authorized personnel or systems when classified items appear on a system.

The detection mechanism provides automatic classification of artifacts based on content. Each artifact has a classification state associated with it, and typically the artifact that is in a certain condition is in one of a number of classification states depending on a prior classification state, with different policy allowed to be attached to each state. Preferably, the technique works by applying rules to classes of artifacts.

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.

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.

In a representative embodiment, the artifact state machine described above is 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 DLP solution.

The 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 determine policies applicable to a particular endpoint.

The described functionality may be implemented as an adjunct or extension to an existing DLP solution including, without limitation, an DLP client endpoint, a DLP server, or the like.

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.

The techniques disclosed herein are not limited to a middleware DLP appliance that monitors network traffic such as has been described, but this will be a typical implementation. The above-described information classification change detection 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.

The term “artifact” should be broadly construed to refer to an item or object of interest (including its content) to a DLP system, policy, component, program or process.

Having described our invention, what we now claim is as follows.