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

arXiv:2607.24177 · cs.CR, cs.LG · Submitted 2026-07-27 · Read on arXiv

Andrea Ponte, Daniel Gibert, Matous Kozak, Dmitrijs Trizna, Maura Pintor, Battista Biggio, Fabio Roli, Luca Demetrio

cs.CR, cs.LG

Submitted: 2026-07-27

Code: https://github.com/zangobot/exebenchmark

Project page: https://exebench.github.io

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Robustness — 47× in this paper · explained in 5 episodes
• Benchmark — 34× in this paper · explained in 2 episodes
• Adversarial Attacks — 18× in this paper · explained in 1 episode
• Accuracy — 15× in this paper · explained in 1 episode
• F1 Score — 10× in this paper · explained in 3 episodes
• Adversarial Robustness — 7× in this paper · explained in 3 episodes
• Feature Engineering — 7× in this paper · explained in 3 episodes
• AUC — 4× in this paper · explained in 2 episodes
• De-Randomized Smoothing — 4× in this paper
• Detection Rate — 4× in this paper
• Feature Extraction — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Adversarial Examples — 3× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Computational overhead — 3× in this paper · explained in 2 episodes
• Concept Drift — 3× in this paper · explained in 4 episodes
• Adversarial Training — 2× in this paper · explained in 1 episode
• False Positive Rate — 2× in this paper
• Gradient Boosting Decision Tree — 2× in this paper
• Transferability — 2× in this paper · explained in 4 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Future Artificial Intelligence Research — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Windows Portable Executable — 1× in this paper

Sources

• Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing

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