SYSTEMS AND METHODS FOR IDENTIFYING POTENTIAL MISUSE OR EXFILTRATION OF DATA
Provided herein are systems and methods for preventing or controlling data movement. A learning engine may detect capabilities of a computing environment for allowing data access or transfer, and activities relating to data access or transfer from the computing environment. Data assets of the computing environment that are protected may be identified, according to metadata of the data assets. The learning engine may, according to the identified data assets and at least one of the detected capabilities or activities, determine a situation within the computing environment that represents potential or actual exfiltration of one of the identified data assets. A rule engine may perform an action to prevent or control the potential or actual data movement of the one of the identified data assets, responsive to applying one or more rules to the determined situation.
1 . A system for preventing or controlling misuse of data, the system comprising:
a learning engine executing on one or more processors, the learning engine configured to:
detect capabilities of a computing environment for allowing data access or transfer, and activities relating to data access or transfer from, into or through the computing environment; and
determine, according to data assets of the computing environment that are identified to be protected, and at least one of the detected capabilities or activities, a situation within the computing environment that represents potential or actual misuse of one of the identified data assets, wherein the data assets that are to be protected are identified according to metadata of the data assets; and
a rule engine executing on the one or more processors, the rule engine configured to perform an action to prevent or control the potential or actual misuse of the one of the identified data assets, responsive to applying one or more rules to the determined situation.
2 . The system of claim 1 , further comprising training data for use by the learning engine to recognize application or user behavior indicative of potential or actual misuse of data.
3 . The system of claim 1 , wherein the learning engine is configured to detect the capabilities or the activities by monitoring or detecting one or more of: graphical user interface (GUI) controls available to a user control selection by the user, application programming interface (API) calls, files accessed, data communicated over a network, or activity using an input/output (I/O) device.
4 . The system of claim 1 , wherein the learning engine is configured to identify a first data asset that is protected, by monitoring or identifying at least one of: a residing location of the first data asset, an owner of the first data asset, a type of the first data asset, or whether part or all of the first data asset comprises classified or sensitive data.
5 . The system of claim 1 , wherein the computing environment comprises at least one of a web browser, an application, background system service, or an input/output (I/O) device.
6 . The system of claim 5 , wherein the application comprises a cloud-synchronization application, an electronic-mail application, a document processing or rendering application, a data transfer or copying application, or a facsimile or printing application.
7 . The system of claim 1 , wherein the learning engine is configured to detect the capabilities or the activities by detecting meta-data, words or phrases associated with application interfaces indicative of means of data egress from the computing environment.
8 . The system of claim 7 , wherein the learning engine is configured to determine the situation within the computing environment that represents potential or actual misuse of the one of the identified data assets, by relating the detected words or phrases in the application interfaces, to an user action via one or more corresponding application interfaces.
9 . The system of claim 1 , wherein the learning engine is configured to determine whether there is a situation within the computing environment that represents potential or actual exfiltration of one or more of the identified data assets, responsive to a triggering event.
10 . The system of claim 1 , wherein the action to prevent or control the potential or actual misuse of data comprises at least one of: warning or blocking a user against data movement of the one of the identified data assets, or blocking data movement of the one of the identified data assets by an application.
11 . A method for preventing or controlling misuse of data, the method comprising:
detecting, by a learning engine executing on one or more processors, capabilities of a computing environment for allowing data access or transfer, and activities relating to data access or transfer from the computing environment;
identifying data assets of the computing environment that are protected, according to metadata of the data assets;
determining, by the learning engine according to the identified data assets and at least one of the detected capabilities or activities, a situation within the computing environment that represents potential or actual misuse of one of the identified data assets; and
performing, by a rule engine executing on the one or more processors, an action to prevent or control the potential or actual misuse of the one of the identified data assets, responsive to applying one or more rules to the determined situation.
12 . The method of claim 11 , further comprising providing the training data, for use by the learning engine to recognize application or user behavior indicative of potential or actual misuse of data.
13 . The method of claim 11 , wherein detecting the capabilities or the activities comprises monitoring or detecting one or more of: graphical user interface (GUI) controls available to a user, control selection by the user, application programming interface (API) calls, files accessed, data communicated over a network, or activity using an input/output (I/O) device.
14 . The method of claim 11 , further comprising identifying a first data asset that is protected, by monitoring or identifying at least one of: a residing location of the first data asset, an owner of the first data asset, a type of the first data asset, or whether part or all of the first data asset comprises classified or sensitive data.
15 . The method of claim 11 , wherein the computing environment comprises at least one of a web browser, an application, background system service or an input/output (I/O) device.
16 . The method of claim 15 , wherein the application comprises a cloud-synchronization application, an electronic-mail application, a document processing or rendering application, a data transfer or copying application, or a facsimile or printing application.
17 . The method of claim 11 , wherein detecting the capabilities or the activities comprises detecting words or phrases in application interfaces indicative of means of data egress from the computing environment.
18 . The method of claim 17 , wherein determining the situation within the computing environment that represents potential or actual misuse of the one of the identified data assets, comprises relating the detected words or phrases in the application interfaces, to a user action via one or more corresponding application interfaces.
19 . The method of claim 11 , further comprising determining whether there is a situation within the computing environment that represents potential or actual exfiltration of one or more of the identified data assets, responsive to a triggering event.
20 . The method of claim 11 , wherein the action to prevent or control the potential or actual misuse of data comprises at least one of: warning or blocking a user against data movement of the one of the identified data assets, or blocking data movement of the one of the identified data assets by an application.