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公开(公告)号:US20200304535A1
公开(公告)日:2020-09-24
申请号:US16814689
申请日:2020-03-10
Applicant: Booz Allen Hamilton Inc.
Inventor: Aaron SANT-MILLER , Andre Tai NGUYEN , William Hall BADART , Sarah OLSON , Jesse SHANAHAN
Abstract: A method for detecting and/or identifying a cyber-attack on a network can include segmenting the network using a segmentation method with machine learning to generate one or more network segments; assigning a score to a data point within each network segment based on a presence or absence of an identified anomalous behavior of the data point; analyzing network data flow, via behavioral modeling, to provide a context for characterizing the anomalous behavior; combining, via a reinforcement learning agent, outputs of the segmentation method with behavioral modelling and assigned score to detect and/or identify a cyber-attack; providing one or more alerts to an analyst; receiving an analyst assessment of an effectiveness of the detection and/or identification; and providing the analyst assessment as feedback to the reinforcement learning agent.