Leveraging Adversarial Examples to Quantify Membership Information
Leakage

Leveraging Adversarial Examples to Quantify Membership Information Leakage

17 March 2022

Ganesh Del Grosso

Pablo Piantanida

Papers citing "Leveraging Adversarial Examples to Quantify Membership Information Leakage"

17 / 17 papers shown

Title
Mitigating Noise Detriment in Differentially Private Federated Learning with Model Pre-training Huitong Jin Yipeng Zhou Laizhong Cui Quan Z. Sheng AI4CE 48 0 0 18 Aug 2024
Representation Magnitude has a Liability to Privacy Vulnerability Xingli Fang Jung-Eun Kim 19 1 0 23 Jul 2024
SeqMIA: Sequential-Metric Based Membership Inference Attack Hao Li Zheng Li Siyuan Wu Chengrui Hu Yutong Ye Min Zhang Dengguo Feng Yang Zhang 32 3 0 21 Jul 2024
Inference Attacks: A Taxonomy, Survey, and Promising Directions Feng Wu Lei Cui Shaowen Yao Shui Yu 39 2 0 04 Jun 2024
Center-Based Relaxed Learning Against Membership Inference Attacks Xingli Fang Jung-Eun Kim 38 2 0 26 Apr 2024
Disposable Transfer Learning for Selective Source Task Unlearning Seunghee Koh Hyounguk Shon Janghyeon Lee H. Hong Junmo Kim 22 2 0 19 Aug 2023
SoK: Comparing Different Membership Inference Attacks with a Comprehensive Benchmark Jun Niu Xiaoyan Zhu Moxuan Zeng Ge Zhang Qingyang Zhao ... Peng Liu Yulong Shen Xiaohong Jiang Jianfeng Ma Yuqing Zhang 42 3 0 12 Jul 2023
Membership Inference Attacks on DNNs using Adversarial Perturbations Hassan Ali Adnan Qayyum Ala I. Al-Fuqaha Junaid Qadir AAML 24 3 0 11 Jul 2023
Membership inference attack with relative decision boundary distance Jiacheng Xu Chengxiang Tan 21 1 0 07 Jun 2023
Watermarking Text Data on Large Language Models for Dataset Copyright Yixin Liu Hongsheng Hu Xun Chen Xuyun Zhang Lichao Sun WaLM 19 22 0 22 May 2023
On the Privacy Effect of Data Enhancement via the Lens of Memorization Xiao-Li Li Qiongxiu Li Zhan Hu Xiaolin Hu 27 13 0 17 Aug 2022
Membership Inference Attacks via Adversarial Examples Hamid Jalalzai Elie Kadoche Rémi Leluc Vincent Plassier AAML FedML MIACV 27 7 0 27 Jul 2022
Bounding Information Leakage in Machine Learning Ganesh Del Grosso Georg Pichler C. Palamidessi Pablo Piantanida MIACV FedML 38 10 0 09 May 2021
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 194 358 0 24 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 314 4,203 0 23 Aug 2019
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,216 0 16 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 275 5,833 0 08 Jul 2016