FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation
Authors: Hanlin Gu, Jiahuan Luo, Yan Kang, Yuan Yao, Gongxi Zhu, Bowen Li, Lixin Fan, Qiang Yang | Published: 2024-06-03
プライバシー保護手法
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients
Authors: Weijun Li, Qiongkai Xu, Mark Dras | Published: 2024-06-03 | Updated: 2024-10-04
A Systematic and Formal Study of the Impact of Local Differential Privacy on Fairness: Preliminary Results
Authors: Karima Makhlouf, Tamara Stefanovic, Heber H. Arcolezi, Catuscia Palamidessi | Published: 2024-05-23
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
Authors: Tudor Cebere, Aurélien Bellet, Nicolas Papernot | Published: 2024-05-23 | Updated: 2024-10-14
Federated Domain-Specific Knowledge Transfer on Large Language Models Using Synthetic Data
Authors: Haoran Li, Xinyuan Zhao, Dadi Guo, Hanlin Gu, Ziqian Zeng, Yuxing Han, Yangqiu Song, Lixin Fan, Qiang Yang | Published: 2024-05-23
Naturally Private Recommendations with Determinantal Point Processes
Authors: Jack Fitzsimons, Agustín Freitas Pasqualini, Robert Pisarczyk, Dmitrii Usynin | Published: 2024-05-22
Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent
Authors: Holger Dette, Carina Graw | Published: 2024-05-21
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
Authors: Tianqu Kang, Lumin Liu, Hengtao He, Jun Zhang, S. H. Song, Khaled B. Letaief | Published: 2024-05-16
Learnable Privacy Neurons Localization in Language Models
Authors: Ruizhe Chen, Tianxiang Hu, Yang Feng, Zuozhu Liu | Published: 2024-05-16
Differentially Private Federated Learning: A Systematic Review
Authors: Jie Fu, Yuan Hong, Xinpeng Ling, Leixia Wang, Xun Ran, Zhiyu Sun, Wendy Hui Wang, Zhili Chen, Yang Cao | Published: 2024-05-14 | Updated: 2024-05-20