306 citations · 851 across the 25 of their papers we have counts for
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cs.LG2023
MalProtect: Stateful Defense Against Adversarial Query Attacks in ML-based Malware Detection
Aqib Rashid, Jose Such
ML models are known to be vulnerable to adversarial query attacks. In these attacks, queries are iteratively perturbed towards a particular class without any knowledge of the targe…
cs.LG2023★ 1 cited
Effectiveness of Moving Target Defenses for Adversarial Attacks in ML-based Malware Detection
Aqib Rashid, Jose Such
Several moving target defenses (MTDs) to counter adversarial ML attacks have been proposed in recent years. MTDs claim to increase the difficulty for the attacker in conducting att…
cs.LG2022
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection
Aqib Rashid, Jose Such
Over the years, most research towards defenses against adversarial attacks on machine learning models has been in the image recognition domain. The ML-based malware detection domai…