Sarah Johnson Olson

US Patent:

20200304535, Sep 24, 2020

Filed:

Mar 10, 2020

Appl. No.:

16/814689

Inventors:

- McLean VA, US
Andre Tai NGUYEN - Seattle WA, US
William Hall BADART - Washington DC, US
Sarah OLSON - Arlington VA, US
Jesse SHANAHAN - Herndon VA, US

Assignee:

Booz Allen Hamilton Inc. - McLean VA

International Classification:

H04L 29/06
G06N 20/00

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.