Published September 28, 2021 | Version v1
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amsqr at MLSEC-2021: Thwarting Adversarial Malware Evasion with a Defense-in-Depth


This paper describes the author's participation in the 3rd edition of the Machine Learning Security Evasion Competition (MLSEC-2021) sponsored by CUJO AI, VM-Ray, MRG-Effitas, Nvidia and Microsoft. As in the previous year the goal was not only developing measures against adversarial attacks on a pre-defined set of malware samples but also finding ways of bypassing other teams' defenses in a simulated cloud environment. The submitted solutions were ranked second in both defender and attacker tracks.



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