/Federated_learning_with_differential_privacy

Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.

Primary LanguagePython

Federated Learning with Differential Privacy

Citation

If you find "federated learning with DP" useful in your research, please consider citing:

@ARTICLE{Wei2020Fed,
author={Kang Wei and Jun Li and Ming Ding and Chuan Ma 
    and Howard H. Yang and Farhad Farokhi and Shi Jin
    and Tony Q. S. Quek and H. Vincent Poor},
journal={{IEEE} Transactions on Information Forensics and Security},
title={Federated Learning with Differential Privacy: {Algorithms} and Performance Analysis},
year={2020},
volume={15},
number={},
pages={3454-3469},}

@ARTICLE{Ma202On,
author={C. {Ma} and J. {Li} and M. {Ding} and H. H. {Yang} and F. {Shu} and T. Q. S. {Quek} and H. V. {Poor}},
title={On Safeguarding Privacy and Security in the Framework of Federated Learning},
journal   = {{IEEE} Network},
volume    = {34},
number    = {4},
pages     = {242-248},
year      = {2020},}

Prerequisites

Python 3.6
Torch 1.5.1

Models&Data

Training

Description