SoK: Unintended Interactions among Machine Learning Defenses and Risks
Authors: Vasisht Duddu, Sebastian Szyller, N. Asokan | Published: 2023-12-07 | Updated: 2024-04-04
Overfitting and Memorization
Why Train More? Effective and Efficient Membership Inference via Memorization
Authors: Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha | Published: 2023-10-12
A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services
Authors: Hongsheng Hu, Shuo Wang, Jiamin Chang, Haonan Zhong, Ruoxi Sun, Shuang Hao, Haojin Zhu, Minhui Xue | Published: 2023-09-15 | Updated: 2024-01-15
Generative Adversarial Networks Unlearning
Authors: Hui Sun, Tianqing Zhu, Wenhan Chang, Wanlei Zhou | Published: 2023-08-19
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
Authors: Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk | Published: 2022-02-02 | Updated: 2022-11-30
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning
Authors: Vasisht Duddu, Sebastian Szyller, N. Asokan | Published: 2021-12-04 | Updated: 2022-09-05
On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models
Authors: Benjamin Zi Hao Zhao, Aviral Agrawal, Catisha Coburn, Hassan Jameel Asghar, Raghav Bhaskar, Mohamed Ali Kaafar, Darren Webb, Peter Dickinson | Published: 2021-03-12
How benign is benign overfitting?
Authors: Amartya Sanyal, Puneet K Dokania, Varun Kanade, Philip H. S. Torr | Published: 2020-07-08