• Corpus ID: 167217608

ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

  title={ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation},
  author={Yuzhe Yang and Guo Zhang and Dina Katabi and Zhi Xu},
Deep neural networks are vulnerable to adversarial attacks. [] Key Method In ME-Net, images are preprocessed using two steps: first pixels are randomly dropped from the image; then, the image is reconstructed using ME. We show that this process destroys the adversarial structure of the noise, while re-enforcing the global structure in the original image. Since humans typically rely on such global structures in classifying images, the process makes the network mode compatible with human perception. We conduct…

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Unsupervised Perturbation based Self-Supervised Adversarial Training

  • Zhuoyi WangYu Lin B. Thuraisingham
  • Computer Science
    2021 7th IEEE Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS)
  • 2021
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