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Topic Glass-box ML

June 10, 2020July 23, 2020

Learning from Context: A Multi-view Deep Learning Architecture for Malware Detection

Machine learning (ML) used for static portable executable (PE) malware detection typically employs per-file numerical feature vector representations as input […]

Adarsh Kyadige
Ethan Rudd
Konstantin Berlin

Interpretable ML

Our interpretable ML research focuses on inventing, prototyping, and operationalizing methods to explain the “thought processes” of our security machine learning systems. This work has resulted in multiple successful commercial model shipments and patents.

August 8, 2018July 23, 2020

Measuring the Speed of the Red Queen’s Race; Adaption and Evasion in Malware

Security is a constant cat-and-mouse game between those trying to keep abreast of and detect novel malware, and the authors […]

Richard Harang
Felipe Ducau
July 23, 2017July 23, 2020

Getting Insight Out Of and Back Into Deep Neural Networks

Deep learning has emerged as a powerful tool for classifying malicious software artifacts, however the generic black-box nature of these […]

Richard Harang
Sophos AI - Smarter Security
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