Amplifying Membership Exposure via Data Poisoning
Authors: Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang | Published: 2022-11-01
Membership Inference
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
Authors: Chuan Guo, Alexandre Sablayrolles, Maziar Sanjabi | Published: 2022-10-24 | Updated: 2023-08-10
On the Robustness of Dataset Inference
Authors: Sebastian Szyller, Rui Zhang, Jian Liu, N. Asokan | Published: 2022-10-24 | Updated: 2023-06-19
Extracted BERT Model Leaks More Information than You Think!
Authors: Xuanli He, Chen Chen, Lingjuan Lyu, Qiongkai Xu | Published: 2022-10-21 | Updated: 2022-10-31
How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers
Authors: Guangsheng Zhang, Bo Liu, Huan Tian, Tianqing Zhu, Ming Ding, Wanlei Zhou | Published: 2022-10-20 | Updated: 2024-02-02
An Empirical Analysis of SMS Scam Detection Systems
Authors: Muhammad Salman, Muhammad Ikram, Mohamed Ali Kaafar | Published: 2022-10-19
A General Framework for Auditing Differentially Private Machine Learning
Authors: Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa | Published: 2022-10-16 | Updated: 2023-01-06
Distribution inference risks: Identifying and mitigating sources of leakage
Authors: Valentin Hartmann, Léo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West | Published: 2022-09-18
Dataset Inference for Self-Supervised Models
Authors: Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot | Published: 2022-09-16 | Updated: 2023-01-13
Data Privacy and Trustworthy Machine Learning
Authors: Martin Strobel, Reza Shokri | Published: 2022-09-14