Cyberpoint International LLC

James L Ulrich

Mark V Raugas

Rebecca A Borbely

Michael W West

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for assessing cyber threats. In some implementations, data indicating a time window is received. Data indicating at least one dynamic Bayesian network (DBN) is accessed. A plurality of simulations are performed using the DBN, and outcomes of the plurality of simulations are sampled according to the state of the DBN representing the end of the time window. Based on the sampled outcomes of the simulations, a measure of impact of the computer-based threats to the organization over the time window is determined. The determined measure is provided for output to a user.

Assessment of cyber threats

Methods, system, and media for detecting malware are disclosed. A network may be monitored to collect samples of the network traffic. Feature vectors may be extracted from the sampled network traffic. One or more machine learning models may be applied to the feature vectors to produce a score indicative of the presence of a particular type of malware. One or more scores obtained by applying the machine learning models may be fused by another machine learning model into a resulting score. A threshold value may be calculated to accompany a score indicating the likelihood that the traffic sample indicates the presence of malware and the likely effectiveness of planned remediation effort. An alert may be generated from the score and the threshold when the threshold is acceded.

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Potomac, MD, United States of America

James L Ulrich