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Evaluating and Understanding the Robustness of Adversarial Logit Pairing

2018-07-26Code Available0· sign in to hype

Logan Engstrom, Andrew Ilyas, Anish Athalye

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Abstract

We evaluate the robustness of Adversarial Logit Pairing, a recently proposed defense against adversarial examples. We find that a network trained with Adversarial Logit Pairing achieves 0.6% accuracy in the threat model in which the defense is considered. We provide a brief overview of the defense and the threat models/claims considered, as well as a discussion of the methodology and results of our attack, which may offer insights into the reasons underlying the vulnerability of ALP to adversarial attack.

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