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Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. (arXiv:2207.05548v1 [cs.CR])
July 13, 2022, 1:20 a.m. | Luca Demetrio, Battista Biggio, Fabio Roli
cs.CR updates on arXiv.org arxiv.org
While machine learning is vulnerable to adversarial examples, it still lacks
systematic procedures and tools for evaluating its security in different
application contexts. In this article, we discuss how to develop automated and
scalable security evaluations of machine learning using practical attacks,
reporting a use case on Windows malware detection.
adversarial attacks case machine machine learning malware study windows windows malware
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