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Defensive Distillation is Not Robust to Adversarial Examples

14 July 2016
Nicholas Carlini
D. Wagner
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Abstract

We show that defensive distillation is not secure: it is no more resistant to targeted misclassification attacks than unprotected neural networks.

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