SecGNN: Privacy-Preserving Graph Neural Network Training and Inference as a Cloud Service
Authors: Songlei Wang, Yifeng Zheng, Xiaohua Jia | Published: 2022-02-16 | Updated: 2023-01-31
プライバシー保護プロトコル
Local Differential Privacy for Federated Learning
Authors: M. A. P. Chamikara, Dongxi Liu, Seyit Camtepe, Surya Nepal, Marthie Grobler, Peter Bertok, Ibrahim Khalil | Published: 2022-02-12 | Updated: 2022-08-03
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
Efficient Privacy Preserving Logistic Regression for Horizontally Distributed Data
Authors: Guanhong Miao | Published: 2022-02-05 | Updated: 2022-07-20
Training Differentially Private Models with Secure Multiparty Computation
Authors: Sikha Pentyala, Davis Railsback, Ricardo Maia, Rafael Dowsley, David Melanson, Anderson Nascimento, Martine De Cock | Published: 2022-02-05 | Updated: 2022-09-01
Linear Model Against Malicious Adversaries with Local Differential Privacy
Authors: Guanhong Miao, A. Adam Ding, Samuel S. Wu | Published: 2022-02-05 | Updated: 2022-06-29
Transfer Learning In Differential Privacy’s Hybrid-Model
Authors: Refael Kohen, Or Sheffet | Published: 2022-01-28 | Updated: 2022-06-16
An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications
Authors: Hitoshi Kiya, AprilPyone MaungMaung, Yuma Kinoshita, Shoko Imaizumi, Sayaka Shiota | Published: 2022-01-26 | Updated: 2022-04-16
Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
Authors: Yipeng Zhou, Xuezheng Liu, Yao Fu, Di Wu, Chao Li, Shui Yu | Published: 2021-07-05