Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models
Authors: Xinlei He, Zheng Li, Weilin Xu, Cory Cornelius, Yang Zhang | Published: 2022-08-22
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Defending against Reconstruction Attacks with Rényi Differential Privacy
Authors: Pierre Stock, Igor Shilov, Ilya Mironov, Alexandre Sablayrolles | Published: 2022-02-15
Membership Inference Attacks and Defenses in Neural Network Pruning
Authors: Xiaoyong Yuan, Lan Zhang | Published: 2022-02-07 | Updated: 2022-08-03
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
DP-UTIL: Comprehensive Utility Analysis of Differential Privacy in Machine Learning
Authors: Ismat Jarin, Birhanu Eshete | Published: 2021-12-24
FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries
Authors: Seng Pei Liew, Tsubasa Takahashi | Published: 2020-10-27
Investigating Membership Inference Attacks under Data Dependencies
Authors: Thomas Humphries, Simon Oya, Lindsey Tulloch, Matthew Rafuse, Ian Goldberg, Urs Hengartner, Florian Kerschbaum | Published: 2020-10-23 | Updated: 2023-06-14
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Authors: Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan Lavista Ferres | Published: 2020-09-11 | Updated: 2022-10-12
Quantifying Membership Inference Vulnerability via Generalization Gap and Other Model Metrics
Authors: Jason W. Bentley, Daniel Gibney, Gary Hoppenworth, Sumit Kumar Jha | Published: 2020-09-11
Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning
Authors: Yang Zou, Zhikun Zhang, Michael Backes, Yang Zhang | Published: 2020-09-10