Generating Adversarial Examples with Adversarial Networks

  title={Generating Adversarial Examples with Adversarial Networks},
  author={Chaowei Xiao and Bo Li and Jun-Yan Zhu and Warren He and Mingyan Liu and Dawn Xiaodong Song},
Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples resulting from adding small-magnitude perturbations to inputs. Such adversarial examples can mislead DNNs to produce adversary-selected results. Different attack strategies have been proposed to generate adversarial examples, but how to produce them with high perceptual quality and more efficiently requires more research efforts. In this paper, we propose AdvGAN to generate adversarial examples with generative… CONTINUE READING
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