FLock: Robust and Privacy-Preserving Federated Learning based on Practical Blockchain State Channels.

Ruonan Chen|Ye Dong|Yizhong Liu|Tingyu Fan|Dawei Li|Zhenyu Guan|Jianwei Liu|Jianying Zhou


Anthology ID:DBLP:conf/www/ChenDLF0G0025
Volume:Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025
Year:2025
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:884-895
URL:https://doi.org/10.1145/3696410.3714666
DOI:https://doi.org/10.1145/3696410.3714666
DBLP:conf/www/ChenDLF0G0025
BibTeX:
@inproceedings{chen-2025-flock, author = {Ruonan Chen and Ye Dong and Yizhong Liu and Tingyu Fan and Dawei Li and Zhenyu Guan and Jianwei Liu and Jianying Zhou}, editor = {Guodong Long and Michale Blumestein and Yi Chang and Liane Lewin-Eytan and Zi Huang and Elad Yom-Tov}, title = {{FLock: Robust and Privacy-Preserving Federated Learning based on Practical Blockchain State Channels}}, booktitle = {{Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025}}, pages = {884--895}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3696410.3714666}, doi = {https://doi.org/10.1145/3696410.3714666} }