NeurIPS 2020Poster
On Adaptive Attacks to Adversarial Example Defenses
作者: Florian Tramer, Nicholas Carlini, Wieland Brendel, Aleksander Madry
摘要
Adaptive attacks have (rightfully) become the de facto standard for evaluating defenses to adversarial examples. We find, however, that typical adaptive evaluations are incomplete. We demonstrate that 13 defenses recently published at ICLR, ICML and NeurIPS---and which illustrate a diverse set of defense strategies---can be circumvented despite attempting to perform evaluations using adaptive attacks.