Federated Learning for Tabular Data: Exploring Potential Risk to Privacy
Authors: Han Wu, Zilong Zhao, Lydia Y. Chen, Aad van Moorsel | Published: 2022-10-13
プライバシーリスク管理
Data Privacy and Trustworthy Machine Learning
Authors: Martin Strobel, Reza Shokri | Published: 2022-09-14
Inferring Sensitive Attributes from Model Explanations
Authors: Vasisht Duddu, Antoine Boutet | Published: 2022-08-21 | Updated: 2022-09-07
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy
Authors: Wenqiang Ruan, Mingxin Xu, Wenjing Fang, Li Wang, Lei Wang, Weili Han | Published: 2022-08-18
FedPerm: Private and Robust Federated Learning by Parameter Permutation
Authors: Hamid Mozaffari, Virendra J. Marathe, Dave Dice | Published: 2022-08-16
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