REPLICANT: Learning Policies for Evading and Hardening Malware Detectors
This work presents Replicant, a deep reinforcement learning framework that learns the realistic task of evasion under a strict label-only black-box threat model and demonstrates that learning the task of evasion not only results in stronger attack performance but provides a better signal for hardening malware detectors.
Shae McFadden, Ilias Tsingenopoulos, Mario D'Onghia et al.
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