Preprint
Sep 2026
Breaking Windows Malware Detection: A Comprehensive Evaluation of Problem-Space Adversarial Robustness
Problem-space evasion attacks have exposed critical weaknesses in machine learning-based malware detectors; yet, their evaluation remains fragmented across models, datasets, and attack methodologies, often neglecting domain-specific requirements such as executability and functionality preservation. We address this gap...
Mashal Zainab, Salijona Dyrmishi, Hamid Bostani et al.
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