In this repository, code is for our AAAI 2023 paper Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning
Install Pytorch
- we can use Visdom to monitor the training progress.
python -m visdom.server -p 8098
- run experiments for the CIFAR-100 dataset:
python main.py --params utils/X.yaml
X = mkrum, foolsgold or bulyan.
Parameters can be changed in those yaml files to reproduce our experiments.
Stay tuned for further updates, thanks!
If you find our work useful in your research, please consider citing:
@inproceedings{DBLP:conf/aaai/LyuHWLWL023,
author = {Xiaoting Lyu and
Yufei Han and
Wei Wang and
Jingkai Liu and
Bin Wang and
Jiqiang Liu and
Xiangliang Zhang},
title = {Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against
Federated Learning},
booktitle = {Thirty-Seventh {AAAI} Conference on Artificial Intelligence, {AAAI}
2023, Thirty-Fifth Conference on Innovative Applications of Artificial
Intelligence, {IAAI} 2023, Thirteenth Symposium on Educational Advances
in Artificial Intelligence, {EAAI} 2023, Washington, DC, USA, February
7-14, 2023},
pages = {9020--9028},
publisher = {{AAAI} Press},
year = {2023},
url = {https://doi.org/10.1609/aaai.v37i7.26083},
doi = {10.1609/AAAI.V37I7.26083},
timestamp = {Mon, 04 Sep 2023 16:50:26 +0200},
biburl = {https://dblp.org/rec/conf/aaai/LyuHWLWL023.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}