Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks

USENIX Security Symposium, pp. 321-338, 2019.

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Other Links: academic.microsoft.com|dblp.uni-trier.de|arxiv.org

Abstract:

Transferability captures the ability of an attack against a machine-learning model to be effective against a different, potentially unknown, model. Empirical evidence for transferability has been shown in previous work, but the underlying reasons why an attack transfers or not are not yet well understood. In this paper, we present a compr...More

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