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arXiv · 2207.05548

Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware

Luca Demetrio·Battista Biggio·Fabio Roli
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Abstract

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.

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Luca Demetrio, Battista Biggio, Fabio Roli. 2022-07-12. Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. https://doi.org/10.1109/msec.2022.3182356

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