Breaking State-of-the-Art Poisoning Defenses to Federated Learning: An Optimization-Based Attack Framework.

Yuxin Yang|Qiang Li|Chenfei Nie|Yuan Hong|Binghui Wang


Anthology ID:DBLP:conf/cikm/Yang0NHW24
Volume:Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024
Year:2024
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:2930-2939
URL:https://doi.org/10.1145/3627673.3679566
DOI:https://doi.org/10.1145/3627673.3679566
DBLP:conf/cikm/Yang0NHW24
BibTeX:
@inproceedings{yang-2024-breaking, author = {Yuxin Yang and Qiang Li and Chenfei Nie and Yuan Hong and Binghui Wang}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{Breaking State-of-the-Art Poisoning Defenses to Federated Learning: An Optimization-Based Attack Framework}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {2930--2939}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679566}, doi = {https://doi.org/10.1145/3627673.3679566} }