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Disparate Vulnerability to Membership Inference Attacks

Proceedings on Privacy Enhancing Technologies (PoPETs), 2019

2 June 2019

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Papers citing "Disparate Vulnerability to Membership Inference Attacks"

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Title
The Tail Tells All: Estimating Model-Level Membership Inference Vulnerability Without Reference Models Euodia Dodd Nataša Krčo Igor Shilov Yves-Alexandre de Montjoye 97 0 0 22 Oct 2025
SMOTE and Mirrors: Exposing Privacy Leakage from Synthetic Minority Oversampling Georgi Ganev Reza Nazari Rees Davison Amir Dizche Xinmin Wu Ralph Abbey Jorge Silva Emiliano De Cristofaro 129 0 0 16 Oct 2025
On the Fairness of Privacy Protection: Measuring and Mitigating the Disparity of Group Privacy Risks for Differentially Private Machine Learning Zhi Yang Changwu Huang Ke Tang Xin Yao 194 0 0 10 Oct 2025
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy B. Kulynych Juan Felipe Gomez G. Kaissis Jamie Hayes Borja Balle Flavio du Pin Calmon Jean Louis Raisaro 176 1 0 09 Jul 2025
Spurious Privacy Leakage in Neural Networks Chenxiang Zhang Jun Pang S. Mauw 307 0 0 26 May 2025
Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy Rushabh Solanki Meghana Bhange Ulrich Aïvodji Elliot Creager 159 3 0 09 May 2025
Disparate Privacy Vulnerability: Targeted Attribute Inference Attacks and Defenses Ehsanul Kabir Lucas Craig Shagufta Mehnaz MIACV AAML 305 1 0 05 Apr 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond Qiongxiu Li Xiaoyu Luo Yiyi Chen Johannes Bjerva 475 4 0 10 Mar 2025
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 272 2 0 01 Jun 2024
"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data GenerationUSENIX Security Symposium (USENIX Security), 2024 Meenatchi Sundaram Muthu Selva Annamalai Georgi Ganev Emiliano De Cristofaro 260 16 0 16 May 2024
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 247 8 0 22 Dec 2023
SoK: Memorisation in machine learning Dmitrii Usynin Moritz Knolle Georgios Kaissis 257 1 0 06 Nov 2023
Why Train More? Effective and Efficient Membership Inference via Memorization Jihye Choi Shruti Tople Varun Chandrasekaran Somesh Jha TDI FedML 182 3 0 12 Oct 2023
Information Leakage from Data Updates in Machine Learning Models Tian Hui Farhad Farokhi Olga Ohrimenko FedML AAML KELM MIACV 182 2 0 20 Sep 2023
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 184 18 0 21 Aug 2023
Investigating the Effect of Misalignment on Membership Privacy in the White-box SettingProceedings on Privacy Enhancing Technologies (PoPETs), 2023 Ana-Maria Cretu Daniel Jones Yves-Alexandre de Montjoye Shruti Tople AAML 158 8 0 08 Jun 2023
Membership Inference Attacks against Synthetic Data through Overfitting DetectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 B. V. Breugel Hao Sun Zhaozhi Qian M. Schaar 184 64 0 24 Feb 2023
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine LearningIEEE Symposium on Security and Privacy (IEEE S&P), 2022 A. Salem Giovanni Cherubin David Evans Boris Köpf Andrew Paverd Anshuman Suri Shruti Tople Santiago Zanella Béguelin 354 55 0 21 Dec 2022
Membership Inference Attacks Against Semantic Segmentation Models Tomás Chobola Dmitrii Usynin Georgios Kaissis MIACV 165 10 0 02 Dec 2022
On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target ModelsIEEE Transactions on Dependable and Secure Computing (TDSC), 2022 Mauro Conti Jiaxin Li S. Picek MIALM 213 3 0 28 Oct 2022
Measuring Forgetting of Memorized Training ExamplesInternational Conference on Learning Representations (ICLR), 2022 Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 344 132 0 30 Jun 2022
Bayesian Estimation of Differential PrivacyInternational Conference on Machine Learning (ICML), 2022 Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople A. Salem Victor Rühle Andrew Paverd Mohammad Naseri Boris Köpf Daniel Jones 232 47 0 10 Jun 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu Gautam Kamath Janardhan Kulkarni Tie-Yan Liu Jian Yin Huishuai Zhang 468 24 0 06 Jun 2022
Fair NLP Models with Differentially Private Text EncodersConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 Gaurav Maheshwari Pascal Denis Mikaela Keller A. Bellet FedML SILM 103 16 0 12 May 2022
What You See is What You Get: Principled Deep Learning via Distributional GeneralizationNeural Information Processing Systems (NeurIPS), 2022 B. Kulynych Yao-Yuan Yang Yaodong Yu Jarosław Błasiok Preetum Nakkiran OOD 250 11 0 07 Apr 2022
Formalizing and Estimating Distribution Inference Risks Anshuman Suri David Evans MIACV 355 56 0 13 Sep 2021
Fairness Properties of Face Recognition and Obfuscation SystemsUSENIX Security Symposium (USENIX Security), 2021 Harrison Rosenberg Brian Tang Kassem Fawaz S. Jha PICV 115 17 0 05 Aug 2021
Investigating Membership Inference Attacks under Data Dependencies Thomas Humphries Simon Oya Lindsey Tulloch Matthew Rafuse I. Goldberg Urs Hengartner Florian Kerschbaum MIACV MIALM 566 42 0 23 Oct 2020