ResearchPapers/fawkes
ResearchPapers/fawkes
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Shawn-Shan e9f1a50653 0.0.6 
Former-commit-id: 14c0173d9f573e7ccb275b3e366505057ac2c9b1 [formerly e359682d967212b4b3f27923fd659bbade7880e5]
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2020-07-07 11:14:38 -05:00
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__pycache__ 0.0.6 2020-07-07 11:14:38 -05:00
__init__.py 0.0.6 2020-07-07 11:14:38 -05:00
__main__.py cli 2020-07-02 12:32:05 -05:00
align_face.py 0.0.6 2020-07-07 11:14:38 -05:00
detect_faces.py 0.0.6 2020-07-07 11:14:38 -05:00
differentiator.py 0.0.6 2020-07-07 11:14:38 -05:00
protection.py 0.0.6 2020-07-07 11:14:38 -05:00
README.md 0.0.1 2020-06-29 11:14:48 -05:00
utils.py 0.0.6 2020-07-07 11:14:38 -05:00

README.md

Fawkes

This application is built for individuals to cloak their images before uploading to the Internet. For more information about the project, please refer to our project webpage.

If you are a developer or researcher planning to customize and modify on our existing code. Please refer to fawkes_dev.

How do I protect my images?

TBD

Citation

@inproceedings{shan2020fawkes,
  title={Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models},
  author={Shan, Shawn and Wenger, Emily and Zhang, Jiayun and Li, Huiying and Zheng, Haitao and Zhao, Ben Y},
  booktitle="Proc. of USENIX Security",
  year={2020}
}

Code implementation of the paper "Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models", at USENIX Security 2020.