Charles River Analytics, Inc.

Michael Howard

Avi Pfeffer

Mukesh Dalal

Michael Reposa

Methods and systems for Predictive Malware Defense (PMD) are described. The systems and methods can utilize advanced machine-learning (ML) techniques to generate malware defenses preemptively. Embodiments of PMD can utilize models, which are trained on features extracted from malware families, to predict possible courses of malware evolution. PMD captures these predicted future evolutions in signatures of as yet unseen malware variants to function as a malware vaccine. These signatures of predicted future malware 'evolutions' can be added to the training set of a machine-learning (ML) based malware detection and/or mitigation system so that it can detect these new variants as they arrive.

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Watertown, MA, United States of America

Michael Howard