Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks
arXiv:2604.20495v1 Announce Type: cross
Abstract: Machine learning-based static malware detectors remain vulnerable to adversarial evasion techniques, such as metamorphic engine mutations. To address this vulnerability, we propose a certifiably robust…