Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding.
Yuke Hu|Wei Liang|Ruofan Wu|Kai Xiao|Weiqiang Wang|Xiaochen Li|Jinfei Liu|Zhan Qin
| Anthology ID: | DBLP:conf/www/HuLWXWLLQ23 |
|---|---|
| Volume: | Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023 |
| Year: | 2023 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 2306-2317 |
| URL: | https://doi.org/10.1145/3543507.3583450 |
| DOI: | https://doi.org/10.1145/3543507.3583450 |
| DBLP: | conf/www/HuLWXWLLQ23 |
| BibTeX: |
@inproceedings{hu-2023-quantifying,
author = {Yuke Hu and
Wei Liang and
Ruofan Wu and
Kai Xiao and
Weiqiang Wang and
Xiaochen Li and
Jinfei Liu and
Zhan Qin},
editor = {Ying Ding and
Jie Tang and
Juan F. Sequeda and
Lora Aroyo and
Carlos Castillo and
Geert-Jan Houben},
title = {{Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding}},
booktitle = {{Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}},
pages = {2306--2317},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3543507.3583450},
doi = {https://doi.org/10.1145/3543507.3583450}
}