ResearchPapers/fawkes
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# Fawkes
# Fawkes Binary
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](http://sandlab.cs.uchicago.edu/fawkes/).
If you are a developer or researcher planning to customize and modify on our existing code. Please refer to [fawkes_dev](https://github.com/Shawn-Shan/fawkes/tree/master/fawkes_dev).
If you are a developer or researcher planning to customize and modify on our existing code. Please refer to [fawkes](https://github.com/Shawn-Shan/fawkes/tree/master/).
### How to Setup
#### MAC:
* Download the binary following this [link](http://sandlab.cs.uchicago.edu/fawkes/files/fawkes_binary.zip) and unzip the download file.
*
* Create a directory and move all the images you wish to protect into that directory. Note the path to that directory (e.g. ~/Desktop/images).
* Open [terminal](https://support.apple.com/guide/terminal/open-or-quit-terminal-apd5265185d-f365-44cb-8b09-71a064a42125/mac) and change directory to fawkes (the unzipped folder).
* (If your MacOS is Catalina) Run `sudo spctl --master-disable` to enable running apps from unidentified developer.
* Run `./fawkes -d IMAGE_DIR_PATH -m low` to generate cloak for images in `IMAGE_DIR_PATH`.
* More details on the optional parameters check out the [github repo](https://github.com/Shawn-Shan/fawkes/tree/master/).
# How do I protect my images?
#### PC:
More details coming soon. The steps should be similar to the MAC setup.
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](https://arxiv.org/pdf/2002.08327.pdf)", at *USENIX Security 2020*.