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most citedA Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing

11 citations · 30 across the 7 of their papers we have counts for

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cs.CR2026

EXE-Bench: Ranking the Tradeoffs of AI-based Windows Malware Detectors for Real-World Usability

Andrea Ponte, Daniel Gibert, Matous Kozak +5

Due to the lack of systematic evaluations, we are not yet able to determine which AI-based Windows malware detector to deploy in production, since existing evaluations (i) differ i…