This is the code for TPDS-2022-09-0583
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Go to DP_code folder
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First install the conda environment with environment.yml.
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Then run create_FLdistribution.sh to create a client distribution first (each client has two shards). The distribution file xxx_1000_clients.pkl would appear in the client folder and you may run the rest.
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This code includes both the participation-level Fed-SDP (FedSDP.py), instance-level Fed-CDP baseline (Fed_CDP_fixed.py) and Fed-DP dynamic(Fed_CDP_dynamic.py) . You may adjust the few lines within the local training for l2-max sensitivity (default fixed clipping sensitivity) and dynamic noise scale (default fixed noise scale). The privacy accounting approach is also provided for
$\epsilon$ privacy spending in Fed-CDP.
Go to gradient_leakage/ folder for gradient leakage attacks on MNIST, Fashion-MNIST, CIFAR10 and LFW (both type 1 leakage and type 2 leakage).
If you are interested in our research, please cite:
@inproceedings{wei2020framework,
title={A framework for evaluating client privacy leakages in federated learning},
author={Wei, Wenqi and Liu, Ling and Loper, Margaret and Chow, Ka-Ho and Gursoy, Mehmet Emre and Truex, Stacey and Wu, Yanzhao},
booktitle={European Symposium on Research in Computer Security},
year={2020},
publisher={Springer}
}
@inproceedings{wei2021gradient,
title={Gradient-Leakage Resilient Federated Learning},
author={Wei, Wenqi and Liu, Ling and Wu, Yanzhao and Su, Gong and Iyengar, Arun},
booktitle={International Conference on Distributed Computing Systems},
year={2021},
publisher={IEEE}}
@ARTICLE{wei2022gradient,
author={Wei, Wenqi and Liu, Ling},
journal={IEEE Transactions on Information Forensics and Security},
title={Gradient Leakage Attack Resilient Deep Learning},
year={2022},
volume={17},
number={},
pages={303-316},
doi={10.1109/TIFS.2021.3139777}}
@ARTICLE{wei2023securing,
author={Wei, Wenqi and Liu, Ling and Zhou, Jingya and Chow, Ka-Ho and Wu, Yanzhao},
journal={IEEE Transactions on Parallel and Distributed Systems},
title={Securing Distributed SGD Against Gradient Leakage Threats},
year={2023},
volume={34},
number={7},
pages={2040-2054},
doi={10.1109/TPDS.2023.3273490}}
}