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InfoResearchPeer-reviewed
MalPurifier: Enhancing Android Malware Detection With Adversarial Purification Against Evasion Attacks
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Summary
MalPurifier is a new adversarial purification framework for Android malware detection, designed to defend ML-based detectors against evasion attacks. It combines a diversified adversarial perturbation mechanism, a protective noise injection strategy, and a Denoising AutoEncoder with a dual-objective loss. Tested on two large-scale datasets, it defended against 37 perturbation-based evasion attacks, keeping robust accuracy above 90.91%.