Enhanced Membership Inference Attacks against Machine Learning Models

18 November 2021

Jiayuan Ye

Aadyaa Maddi

S. K. Murakonda

Vincent Bindschaedler

Papers citing "Enhanced Membership Inference Attacks against Machine Learning Models"

40 / 40 papers shown

Title
The DCR Delusion: Measuring the Privacy Risk of Synthetic Data Zexi Yao Natasa Krco Georgi Ganev Yves-Alexandre de Montjoye 143 0 0 02 May 2025
Do Fairness Interventions Come at the Cost of Privacy: Evaluations for Binary Classifiers Huan Tian Guangsheng Zhang Bo Liu Tianqing Zhu Ming Ding Wanlei Zhou 53 0 0 08 Mar 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text Matthieu Meeus Lukas Wutschitz Santiago Zanella Béguelin Shruti Tople Reza Shokri 80 0 0 24 Feb 2025
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis Junyi Guan Abhijith Sharma Chong Tian Salem Lahlou AAML 49 1 0 18 Feb 2025
SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models Jiawen Zhang Kejia Chen Zunlei Feng Jian Lou Mingli Song Jiaheng Liu Xiaoyu Yang AAML SILM FedML 45 1 0 02 Feb 2025
Detecting Training Data of Large Language Models via Expectation Maximization Gyuwan Kim Yang Li Evangelia Spiliopoulou Jie Ma Miguel Ballesteros William Yang Wang MIALM 95 4 2 10 Oct 2024
Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data Jie Zhang Debeshee Das Gautam Kamath Florian Tramèr MIALM MIACV 235 16 1 29 Sep 2024
On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy Saber Malekmohammadi G. Farnadi 24 2 0 26 Sep 2024
Recent Advances in Attack and Defense Approaches of Large Language Models Jing Cui Yishi Xu Zhewei Huang Shuchang Zhou Jianbin Jiao Junge Zhang PILM AAML 54 1 0 05 Sep 2024
Range Membership Inference Attacks Jiashu Tao Reza Shokri 42 1 0 09 Aug 2024
Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey V. T. Truong Luan Ba Dang Long Bao Le DiffM MedIm 53 16 0 06 Aug 2024
Label Smoothing Improves Machine Unlearning Zonglin Di Zhaowei Zhu Jinghan Jia Jiancheng Liu Zafar Takhirov Bo Jiang Yuanshun Yao Sijia Liu Yang Liu 32 2 0 11 Jun 2024
Adversarial Machine Unlearning Zonglin Di Sixie Yu Yevgeniy Vorobeychik Yang Liu 46 2 0 11 Jun 2024
DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning Yixuan Liu Li Xiong Yuhan Liu Yujie Gu Ruixuan Liu Hong Chen 38 1 0 04 Jun 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 50 3 0 25 Feb 2024
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models Boyang Zhang Zheng Li Ziqing Yang Xinlei He Michael Backes Mario Fritz Yang Zhang 30 4 0 19 Oct 2023
White-box Membership Inference Attacks against Diffusion Models Yan Pang Tianhao Wang Xu Kang Mengdi Huai Yang Zhang AAML DiffM 46 22 0 11 Aug 2023
Node Injection Link Stealing Attack Oualid Zari Javier Parra-Arnau Ayşe Ünsal Melek Önen 34 2 0 25 Jul 2023
Membership inference attack with relative decision boundary distance Jiacheng Xu Chengxiang Tan 26 1 0 07 Jun 2023
PILLAR: How to make semi-private learning more effective Francesco Pinto Yaxian Hu Fanny Yang Amartya Sanyal 46 11 0 06 Jun 2023
Privacy Protectability: An Information-theoretical Approach Siping Shi Bihai Zhang Dan Wang 23 1 0 25 May 2023
Membership Inference Attacks against Synthetic Data through Overfitting Detection B. V. Breugel Hao Sun Zhaozhi Qian M. Schaar 33 45 0 24 Feb 2023
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds Anastasia Borovykh N. Kantas P. Parpas G. Pavliotis 19 1 0 01 Feb 2023
Extracting Training Data from Diffusion Models Nicholas Carlini Jamie Hayes Milad Nasr Matthew Jagielski Vikash Sehwag Florian Tramèr Borja Balle Daphne Ippolito Eric Wallace DiffM 63 569 0 30 Jan 2023
On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models Mauro Conti Jiaxin Li S. Picek MIALM 32 2 0 28 Oct 2022
Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens Georgios Kaissis Alexander Ziller Stefan Kolek Martinez de Azagra Daniel Rueckert 9 0 0 24 Oct 2022
SNAP: Efficient Extraction of Private Properties with Poisoning Harsh Chaudhari John Abascal Alina Oprea Matthew Jagielski Florian Tramèr Jonathan R. Ullman MIACV 34 30 0 25 Aug 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 54 102 0 30 Jun 2022
FEATHERS: Federated Architecture and Hyperparameter Search Jonas Seng P. Prasad Martin Mundt Devendra Singh Dhami Kristian Kersting FedML 49 3 0 24 Jun 2022
Bayesian Estimation of Differential Privacy Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople A. Salem Victor Rühle Andrew J. Paverd Mohammad Naseri Boris Köpf Daniel Jones 17 36 0 10 Jun 2022
Subject Membership Inference Attacks in Federated Learning Anshuman Suri Pallika H. Kanani Virendra J. Marathe Daniel W. Peterson 30 25 0 07 Jun 2022
A Blessing of Dimensionality in Membership Inference through Regularization Jasper Tan Daniel LeJeune Blake Mason Hamid Javadi Richard G. Baraniuk 32 18 0 27 May 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 36 107 0 31 Mar 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) Jiayuan Ye Reza Shokri FedML 27 44 0 10 Mar 2022
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks Fatemehsadat Mireshghallah Kartik Goyal Archit Uniyal Taylor Berg-Kirkpatrick Reza Shokri MIALM 32 151 0 08 Mar 2022
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 29 639 0 07 Dec 2021
Dirichlet Mechanism for Differentially Private KL Divergence Minimization Donlapark Ponnoprat 16 0 0 03 Oct 2021
Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning Maziar Gomrokchi Susan Amin Hossein Aboutalebi Alexander Wong Doina Precup MIACV AAML 39 3 0 08 Sep 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,815 0 14 Dec 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 358 0 24 Mar 2020