FedPerm: Private and Robust Federated Learning by Parameter Permutation
Authors: Hamid Mozaffari, Virendra J. Marathe, Dave Dice | Published: 2022-08-16
プライバシーリスク管理
Practical Vertical Federated Learning with Unsupervised Representation Learning
Authors: Zhaomin Wu, Qinbin Li, Bingsheng He | Published: 2022-08-13
When Does Differentially Private Learning Not Suffer in High Dimensions?
Authors: Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta | Published: 2022-07-01 | Updated: 2022-10-26
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware
Authors: Hanieh Hashemi, Yongqin Wang, Murali Annavaram | Published: 2022-06-30
Private Graph Extraction via Feature Explanations
Authors: Iyiola E. Olatunji, Mandeep Rathee, Thorben Funke, Megha Khosla | Published: 2022-06-29 | Updated: 2023-11-02
The Dark Side: Security Concerns in Machine Learning for EDA
Authors: Zhiyao Xie, Jingyu Pan, Chen-Chia Chang, Yiran Chen | Published: 2022-03-20
Defending against Reconstruction Attacks with Rényi Differential Privacy
Authors: Pierre Stock, Igor Shilov, Ilya Mironov, Alexandre Sablayrolles | Published: 2022-02-15
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
Authors: Alberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford, Zhiwei Steven Wu | Published: 2022-02-10 | Updated: 2022-07-15
PrivFair: a Library for Privacy-Preserving Fairness Auditing
Authors: Sikha Pentyala, David Melanson, Martine De Cock, Golnoosh Farnadi | Published: 2022-02-08 | Updated: 2022-05-23
Membership Inference Attacks and Defenses in Neural Network Pruning
Authors: Xiaoyong Yuan, Lan Zhang | Published: 2022-02-07 | Updated: 2022-08-03