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arxiv 1607.04311 v1 pith:NTODIGS6 submitted 2016-07-14 cs.CR cs.CV

Defensive Distillation is Not Robust to Adversarial Examples

classification cs.CR cs.CV
keywords defensivedistillationadversarialattacksexamplesmisclassificationnetworksneural
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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    Adversarial perturbations possess an inherently low-rank structure that enables more efficient and effective black-box adversarial attacks via subspace projection.