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      Revisiting Role of Autoencoders in Adversarial Settings

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          Abstract

          To combat against adversarial attacks, autoencoder structure is widely used to perform denoising which is regarded as gradient masking. In this paper, we revisit the role of autoencoders in adversarial settings. Through the comprehensive experimental results and analysis, this paper presents the inherent property of adversarial robustness in the autoencoders. We also found that autoencoders may use robust features that cause inherent adversarial robustness. We believe that our discovery of the adversarial robustness of the autoencoders can provide clues to the future research and applications for adversarial defense.

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          Author and article information

          Journal
          21 May 2020
          Article
          2005.10750
          7f176306-fad7-4f9a-a05a-8c013c89c9cf

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          Accepted at ICIP 2020
          cs.CV cs.LG

          Computer vision & Pattern recognition,Artificial intelligence
          Computer vision & Pattern recognition, Artificial intelligence

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