Forcepoint LLC

Arceo Labs Inc.

Forcepoint Federal Holdings LLC

Ann Irvine

Russell Snyder

Richard Anthony Ford

Adam Reeve

Benjamin Shih

Christopher Poirel

Eduardo Luiggi

Chris Poirel

Chris Puderbaugh

Robert Mealey

Brandon L Swafford

David Coffey

Jordan A Dominguez

Kristin Machacek Leary

Determining additional signals for determining cybersecurity risk is disclosed, including: obtaining signals associated with a cybersecurity risk, wherein the obtained signals include technographic signals and query derived signals obtained from queries; combining the technographic signals and the query derived signals into a Bayesian model indicating the cybersecurity risk; and determining additional technographic signals or additional query derived signals associated with the cybersecurity risk to obtain such that the additional technographic signals or the additional query derived signals are to be computed to impact the cybersecurity risk.

Determining additional signals for determining cybersecurity risk

Generating a cybersecurity risk model using sparse data is disclosed, including: obtaining signals associated with a cybersecurity risk, wherein the obtained signals include technographic signals and query derived signals obtained from queries; generating pseudo signals based at least in part on a priori factors relating to the cybersecurity risk; and combining the pseudo signals and the obtained signals into a Bayesian model indicating the cybersecurity risk.

Generating a cybersecurity risk model using sparse data

A method, system and computer-usable medium for constructing a distribution of interrelated event features. The constructing a distribution of interrelated event features includes receiving a stream of events, the stream of events comprising a plurality of events; extracting features from the plurality of events; constructing a distribution of the features from the plurality of events; and, analyzing the distribution of the features from the plurality of events.

Identifying security risks using distributions of characteristic features extracted from a plurality of events

A method, system and computer-usable medium for adaptively assessing risk associated with an endpoint, comprising: determining a risk level corresponding to an entity associated with an endpoint; selecting a frequency and a duration of an endpoint monitoring interval; collecting user behavior to collect user behavior associated with the entity for the duration of the endpoint monitoring interval via the endpoint; processing the user behavior to generate a current risk score for the entity; comparing the current risk score of the user to historical risk scores to determine whether a risk score of a user has changed; and changing the risk score of the user to the current risk score when the risk score of the user has changed.

Gracefully handling endpoint feedback when starting to monitor

A method, system and computer-usable medium are disclosed for identifying security risks to a computer system based on a distribution of categorical features of events. Certain embodiments are directed to a computer-implemented method comprising: receiving a stream of events, the stream of events including a plurality of events; extracting a categorical feature from the plurality of events, where the categorical feature includes a set of categorical feature members, where the set of categorical feature members are generated on the fly from string values included in the extracted categorical feature; constructing a distribution for the categorical feature based on categorical feature members extracted from the plurality of events; and, analyzing the distribution of the categorical feature to identify one or more security risk factors.

A method, system and computer-usable medium for generating session-based security information. Generating the session-based security information includes the steps of monitoring user behavior between an enactor and an entity; detecting user behavior data associated with the user behavior; generating a session using the user behavior data, the session relating to an entity discrete interaction of the enactor; and, associating the session and the session-based security information with the user profile.

Session-based security information

A method, system and computer-usable medium for adaptively remediating multivariate risk, comprising: detecting a violation of a multivariate security policy, the multivariate security policy comprising a plurality of variables; identifying a variable from the plurality of variables associated with a cause of the violation; associating an entity with the variable associated with the cause of the violation; and, adaptively remediating a risk associated with the entity.

Adaptive remediation of multivariate risk

A method, system, and computer-usable medium for protecting against contagion-based risk events are disclosed for monitoring behavior of users to construct a contagion network relationship map of connection and influence relationships between different users and then analyzing a received stream of events from the users to identify a critical event performed by a first user having a first risk score so that one or more propagated risk scores can be generated from the first risk score for at least a first connected user based on connection and influence relationships between the first user and the first connected user that are extracted from the contagion network relationship so that an adaptive response may be automatically generated to protect and control against actions by at least the first connected user based on the one or more propagated risk scores.

Contagion risk detection, analysis and protection

A method, system and computer-usable medium for revising a security policy. Revising the security policy includes detecting an event associated with an entity; providing information relating to the event to a security policy; determining whether the security policy is violated by the event; generating a response when the security policy is violated by the event; and, remediating the security policy to reduce false positive responses generated by the security policy.

Detecting, notifying and remediating noisy security policies

A method, system and computer-usable medium for performing security analytics comprising receiving a stream of data from a data source; preprocessing the stream of data identify entity information and event information from the stream of data; transforming the entity information into transformed entity data and the event information into transformed event data; the transforming conforming to a genericized data model; storing the transformed entity data and the transformed event data in a security analytics data repository; and, performing a security analytics operation on the transformed entity data and the transformed event data.

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Baltimore, MD, United States of America

Ann Irvine