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Triangle Attack: A Query-efficient Decision-based Adversarial Attack. (arXiv:2112.06569v3 [cs.CV] UPDATED)
July 22, 2022, 1:13 a.m. | Xiaosen Wang, Zeliang Zhang, Kangheng Tong, Dihong Gong, Kun He, Zhifeng Li, Wei Liu
cs.CV updates on arXiv.org arxiv.org
Decision-based attack poses a severe threat to real-world applications since
it regards the target model as a black box and only accesses the hard
prediction label. Great efforts have been made recently to decrease the number
of queries; however, existing decision-based attacks still require thousands of
queries in order to generate good quality adversarial examples. In this work,
we find that a benign sample, the current and the next adversarial examples can
naturally construct a triangle in a subspace for …
More from arxiv.org / cs.CV updates on arXiv.org
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