Reversible Watermarking in Deep Convolutional Neural Networks for Integrity Authentication

@article{Guan2020ReversibleWI,
  title={Reversible Watermarking in Deep Convolutional Neural Networks for Integrity Authentication},
  author={Xiquan Guan and Huamin Feng and Weiming Zhang and Hang Zhou and J. Zhang and Nenghai Yu},
  journal={Proceedings of the 28th ACM International Conference on Multimedia},
  year={2020}
}
Deep convolutional neural networks have made outstanding contributions in many fields such as computer vision in the past few years and many researchers published well-trained network for downloading. But recent studies have shown serious concerns about integrity due to model-reuse attacks and backdoor attacks. In order to protect these open-source networks, many algorithms have been proposed such as watermarking. However, these existing algorithms modify the contents of the network permanently… Expand

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