On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks

Ambra Demontis
Ambra Demontis
Maura Pintor
Maura Pintor
Matthew Jagielski
Matthew Jagielski

arXiv: Learning, Volume abs/1809.02861, 2018.

Cited by: 0|Bibtex|Views66
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Transferability captures the ability of an attack against a machine-learning model to be effective against a different, potentially unknown, model. Studying transferability of attacks has gained interest in the last years due to the deployment of cyber-attack detection services based on machine learning. For these applications of machine ...More

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