Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning.
Mingyuan Fan|Yang Liu|Cen Chen|Chengyu Wang|Minghui Qiu|Wenmeng Zhou
| Anthology ID: | DBLP:conf/wsdm/FanLC0QZ24 |
|---|---|
| Volume: | Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 |
| Year: | 2024 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 190-198 |
| URL: | https://doi.org/10.1145/3616855.3635758 |
| DOI: | https://doi.org/10.1145/3616855.3635758 |
| DBLP: | conf/wsdm/FanLC0QZ24 |
| BibTeX: |
@inproceedings{fan-2024-guardian,
author = {Mingyuan Fan and
Yang Liu and
Cen Chen and
Chengyu Wang and
Minghui Qiu and
Wenmeng Zhou},
editor = {Luz Angelica Caudillo-Mata and
Silvio Lattanzi and
Andr\'{e}s Mu\~{n}oz Medina and
Leman Akoglu and
Aristides Gionis and
Sergei Vassilvitskii},
title = {{Guardian: Guarding against Gradient Leakage with Provable Defense for Federated Learning}},
booktitle = {{Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024}},
pages = {190--198},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3616855.3635758},
doi = {https://doi.org/10.1145/3616855.3635758}
}