Data Protection in Deep Learning Era

This GitHub repository summarizes the resources of data protection in deep learning era. We will update this repo regularly.

Dataset Ownership Verification (Copyright Protection)

• Black-box Dataset Ownership Verification via Backdoor Watermarking. [pdf] [code] [Workshop Version]

  • Yiming Li, Mingyan Zhu, Xue Yang, Yong Jiang, Tao Wei, Shu-Tao Xia. IEEE Transactions on Information Forensics and Security, 2023.

• Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection. [pdf] [code]

  • Yiming Li, Yang Bai, Yong Jiang, Yong Yang, Shu-Tao Xia, and Bo Li. NeurIPS, 2022.

• Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking. [pdf] [code]

  • Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, and Xia Hu. arXiv, 2023.

• Radioactive Data: Tracing through Training. [pdf] [code]

  • Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, and Herve Jegou. ICML, 2020.

Dataset Reconstruction (Privacy Protection)

• Dataset Distillation

• Visual Privacy Protection via Mapping Distortion. [pdf] [code]

  • Yiming Li, Peidong Liu, Yong Jiang, Shu-Tao Xia. ICASSP, 2021.