Machine Learning with Membership Privacy using Adversarial Regularization

16 July 2018

Papers citing "Machine Learning with Membership Privacy using Adversarial Regularization"

42 / 92 papers shown

Title
Membership Inference Attacks Against Recommender Systems Minxing Zhang Z. Ren Zihan Wang Pengjie Ren Zhumin Chen Pengfei Hu Yang Zhang MIACV AAML 26 83 0 16 Sep 2021
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning Hongbin Liu Jinyuan Jia Wenjie Qu Neil Zhenqiang Gong 6 94 0 25 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 32 100 0 10 Aug 2021
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning Yi Shi Y. Sagduyu 19 16 0 22 Jul 2021
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 23 71 0 04 Jul 2021
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs Mohammad Malekzadeh Anastasia Borovykh Deniz Gündüz MIACV 26 42 0 25 May 2021
Membership Inference Attacks on Deep Regression Models for Neuroimaging Umang Gupta Dmitris Stripelis Pradeep Lam Paul M. Thompson J. Ambite Greg Ver Steeg MIACV FedML 29 32 0 06 May 2021
A Review of Confidentiality Threats Against Embedded Neural Network Models Raphael Joud Pierre-Alain Moëllic Rémi Bernhard J. Rigaud 28 6 0 04 May 2021
Membership Inference Attacks on Knowledge Graphs Yu Wang Lifu Huang Philip S. Yu Lichao Sun MIACV 30 15 0 16 Apr 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data Runhua Xu Nathalie Baracaldo Yi Zhou Ali Anwar J. Joshi Heiko Ludwig FedML 13 75 0 05 Mar 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 21 51 0 08 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 17 125 0 04 Feb 2021
Practical Blind Membership Inference Attack via Differential Comparisons Bo Hui Yuchen Yang Haolin Yuan Philippe Burlina Neil Zhenqiang Gong Yinzhi Cao MIACV 35 120 0 05 Jan 2021
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 30 14 0 14 Dec 2020
TransMIA: Membership Inference Attacks Using Transfer Shadow Training Seira Hidano Takao Murakami Yusuke Kawamoto MIACV 30 13 0 30 Nov 2020
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes Jinyuan Jia Binghui Wang Neil Zhenqiang Gong AAML 35 5 0 26 Oct 2020
Quantifying Privacy Leakage in Graph Embedding Vasisht Duddu A. Boutet Virat Shejwalkar MIACV 17 119 0 02 Oct 2020
Information Obfuscation of Graph Neural Networks Peiyuan Liao Han Zhao Keyulu Xu Tommi Jaakkola Geoffrey J. Gordon Stefanie Jegelka Ruslan Salakhutdinov AAML 23 34 0 28 Sep 2020
Against Membership Inference Attack: Pruning is All You Need Yijue Wang Chenghong Wang Zigeng Wang Shangli Zhou Hang Liu J. Bi Caiwen Ding Sanguthevar Rajasekaran MIACV 17 48 0 28 Aug 2020
Membership Leakage in Label-Only Exposures Zheng Li Yang Zhang 34 237 0 30 Jul 2020
Anonymizing Machine Learning Models Abigail Goldsteen Gilad Ezov Ron Shmelkin Micha Moffie Ariel Farkash MIACV 16 5 0 26 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 39 213 0 15 Jul 2020
Reducing Risk of Model Inversion Using Privacy-Guided Training Abigail Goldsteen Gilad Ezov Ariel Farkash 30 4 0 29 Jun 2020
When Machine Unlearning Jeopardizes Privacy Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 31 218 0 05 May 2020
Learn to Forget: Machine Unlearning via Neuron Masking Yang Liu Zhuo Ma Ximeng Liu Jian-wei Liu Zhongyuan Jiang Jianfeng Ma Philip Yu K. Ren MU 22 61 0 24 Mar 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 360 0 24 Mar 2020
Dynamic Backdoor Attacks Against Machine Learning Models A. Salem Rui Wen Michael Backes Shiqing Ma Yang Zhang AAML 45 271 0 07 Mar 2020
Assessing differentially private deep learning with Membership Inference Daniel Bernau Philip-William Grassal J. Robl Florian Kerschbaum MIACV FedML 26 23 0 24 Dec 2019
Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation Yang He Shadi Rahimian Bernt Schiele Mario Fritz MIACV 21 49 0 20 Dec 2019
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning Runhua Xu Nathalie Baracaldo Yi Zhou Ali Anwar Heiko Ludwig FedML 21 287 0 12 Dec 2019
Privacy Leakage Avoidance with Switching Ensembles R. Izmailov Peter Lin Chris Mesterharm S. Basu 25 2 0 18 Nov 2019
Alleviating Privacy Attacks via Causal Learning Shruti Tople Amit Sharma A. Nori MIACV OOD 33 32 0 27 Sep 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 235 0 24 May 2019
The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services Yuantian Miao Minhui Xue Chao Chen Lei Pan Jinchao Zhang Benjamin Zi Hao Zhao Dali Kaafar Yang Xiang 19 34 0 17 May 2019
Membership Inference Attacks on Sequence-to-Sequence Models: Is My Data In Your Machine Translation System? Sorami Hisamoto Matt Post Kevin Duh MIACV SLR 30 106 0 11 Apr 2019
Measuring Membership Privacy on Aggregate Location Time-Series Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro 27 23 0 20 Feb 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 22 74 0 08 Jan 2019
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 13 244 0 03 Dec 2018
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models A. Salem Yang Zhang Mathias Humbert Pascal Berrang Mario Fritz Michael Backes MIACV MIALM 41 928 0 04 Jun 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 87 1,455 0 10 May 2018
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks Nicholas Carlini Chang-rui Liu Ulfar Erlingsson Jernej Kos D. Song 89 1,114 0 22 Feb 2018