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Machine Learning (ML) has made unprecedented progress in the past several decades.
Artificial intelligence: a modern approach
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Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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Property inference attacks on fully connected neural networks using permutation invariant representations
Karan Ganju, Qi Wang, Wei Yang, Carl A Gunter, and Nikita Borisov · 2018
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Understanding membership inferences on well-generalized learning models
Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiaofeng Wang, Haixu Tang, Carl A Gunter, and Kai Chen · 2018
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Machine learning with membership privacy using adversarial regularization
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2018
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Privacy risk in machine learning: Analyzing the connection to overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha · 2018
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Logan: Membership inference attacks against generative models
Jamie Hayes, Luca Melis, George Danezis, and Emiliano De Cristofaro · 2019
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Monte carlo and reconstruction membership inference attacks against generative models
Benjamin Hilprecht, Martin Härterich, and Daniel Bernau · 2019
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Performing co-membership attacks against deep generative models
Kin Sum Liu, Chaowei Xiao, Bo Li, and Jie Gao · 2019
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Exploiting unintended feature leakage in collaborative learning
Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov · 2019
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Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2019
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Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models
Ahmed Salem, Yang Zhang, Mathias Humbert, Pascal Berrang, Mario Fritz, and Michael Backes · 2019
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Practical membership inference attack against collaborative inference in industrial iot
Hanxiao Chen, Hongwei Li, Guishan Dong, Meng Hao, Guowen Xu, Xiaoming Huang, and Zhe Liu · 2020
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When machine unlearning jeopardizes privacy
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, and Yang Zhang · 2020
Characterizing membership privacy in stochastic gradient langevin dynamics
Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, and Jun Zhou · 2020
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Gan enhanced membership inference: A passive local attack in federated learning
Jingwen Zhang, Jiale Zhang, Junjun Chen, and Shui Yu · 2020
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Label-only membership inference attacks
Christopher A Choquette-Choo, Florian Tramer, Nicholas Carlini, and Nicolas Papernot · 2021
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Practical blind membership inference attack via differential comparisons
Bo Hui, Yuchen Yang, Haolin Yuan, Philippe Burlina, Neil Zhenqiang Gong, and Yinzhi Cao · 2021
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Encodermi: Membership inference against pre-trained encoders in contrastive learning
Hongbin Liu, Jinyuan Jia, Wenjie Qu, and Neil Zhenqiang Gong · 2021
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Segmentations-leak: Membership inference attacks and defenses in semantic image segmentation
Yang He, Shadi Rahimian, Bernt Schiele, and Mario Fritz · 2020
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Membership leakage in label-only exposures
Zheng Li and Yang Zhang · 2020
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A pragmatic approach to membership inferences on machine learning models
Yunhui Long, Lei Wang, Diyue Bu, Vincent Bindschaedler, Xiaofeng Wang, Haixu Tang, Carl A Gunter, and Kai Chen · 2020
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Privacy risks of general-purpose language models
Xudong Pan, Mi Zhang, Shouling Ji, and Min Yang · 2020
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Sampling attacks: Amplification of membership inference attacks by repeated queries
Shadi Rahimian, Tribhuvanesh Orekondy, and Mario Fritz · 2020
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The secret sharer: Evaluating and testing unintended memorization in neural networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song
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Stealing links from graph neural networks
Xinlei He, Jinyuan Jia, Michael Backes, Neil Zhenqiang Gong, and Yang Zhang
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The audio auditor: user-level membership inference in internet of things voice services
Yuantian Miao, Xue Minhui, Chao Chen, Lei Pan, Jun Zhang, Benjamin Zi Hao Zhao, Dali Kaafar, and Yang Xiang · 2021
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Adversary instantiation: Lower bounds for differentially private machine learning
Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, and Nicholas Carlini · 2021
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On the difficulty of membership inference attacks
Shahbaz Rezaei and Xin Liu · 2021
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On the privacy risks of model explanations
Reza Shokri, Martin Strobel, and Yair Zick · 2021
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Understanding deep learning (still) requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2021
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