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ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

4 June 2018

Mario Fritz

Michael Backes

MIACV

MIALM

ArXiv (abs)PDF HTML

Papers citing "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

42 / 42 papers shown

Title
Unveiling Impact of Frequency Components on Membership Inference Attacks for Diffusion Models Puwei Lian Yujun Cai Songze Li 72 0 0 27 May 2025
Adversarial Attacks in Multimodal Systems: A Practitioner's Survey Shashank Kapoor Sanjay Surendranath Girija Lakshit Arora Dipen Pradhan Ankit Shetgaonkar Aman Raj AAML 133 0 0 06 May 2025
Sharpness-Aware Parameter Selection for Machine Unlearning Saber Malekmohammadi Hong kyu Lee Li Xiong MU 478 0 0 08 Apr 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study Ayana Moshruba Ihsen Alouani Maryam Parsa AAML 114 3 0 24 Feb 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen Xinming Zhang Ninghui Li 301 2 0 28 Jan 2025
Rethinking Membership Inference Attacks Against Transfer Learning Yanwei Yue Jing Chen Qianru Fang Kun He Ziming Zhao Hao Ren Guowen Xu Yang Liu Yang Xiang 115 34 0 20 Jan 2025
SoK: Dataset Copyright Auditing in Machine Learning Systems L. Du Xuanru Zhou M. Chen Chusong Zhang Zhou Su Peng Cheng Jiming Chen Zhikun Zhang MLAU 96 6 0 22 Oct 2024
Poison-splat: Computation Cost Attack on 3D Gaussian Splatting Jiahao Lu Yifan Zhang Qiuhong Shen Xinchao Wang Shuicheng Yan 3DGS 108 2 0 10 Oct 2024
Fine-tuning can Help Detect Pretraining Data from Large Language Models Han Zhang Songxin Zhang Bingyi Jing Hongxin Wei 94 1 0 09 Oct 2024
Fundamental Limits of Membership Inference Attacks on Machine Learning Models Eric Aubinais Elisabeth Gassiat Pablo Piantanida MIACV 84 2 0 20 Oct 2023
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 136 26 0 27 Apr 2020
Differentially Private Data Generative Models Qingrong Chen Chong Xiang Minhui Xue Yue Liu Nikita Borisov Dali Kaafar Haojin Zhu SyDa AAML 59 79 0 06 Dec 2018
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service L. Hanzlik Yang Zhang Kathrin Grosse A. Salem Maximilian Augustin Michael Backes Mario Fritz OffRL 80 102 0 01 Aug 2018
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 49 472 0 16 Jul 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 176 397 0 08 Jun 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 68 164 0 13 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 155 1,474 0 10 May 2018
DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models B. Rouhani Huili Chen F. Koushanfar 99 48 0 02 Apr 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 85 761 0 01 Apr 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 81 286 0 19 Mar 2018
Chiron: Privacy-preserving Machine Learning as a Service T. Hunt Congzheng Song Reza Shokri Vitaly Shmatikov Emmett Witchel 48 201 0 15 Mar 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 141 466 0 14 Feb 2018
Understanding Membership Inferences on Well-Generalized Learning Models Yunhui Long Vincent Bindschaedler Lei Wang Diyue Bu Xiaofeng Wang Haixu Tang Carl A. Gunter Kai Chen MIALM MIACV 55 224 0 13 Feb 2018
Tagvisor: A Privacy Advisor for Sharing Hashtags Yang Zhang Mathias Humbert Tahleen A. Rahman Cheng-Te Li Jun Pang Michael Backes 85 43 0 12 Feb 2018
Towards Measuring Membership Privacy Yunhui Long Vincent Bindschaedler Carl A. Gunter 55 85 0 25 Dec 2017
Machine Learning Models that Remember Too Much Congzheng Song Thomas Ristenpart Vitaly Shmatikov VLM 70 516 0 22 Sep 2017
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification Xiaoyu Cao Neil Zhenqiang Gong AAML 67 210 0 17 Sep 2017
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting Samuel Yeom Irene Giacomelli Matt Fredrikson S. Jha MIACV 106 39 0 05 Sep 2017
walk2friends: Inferring Social Links from Mobility Profiles Michael Backes Mathias Humbert Jun Pang Yang Zhang AAML 53 115 0 28 Aug 2017
Knock Knock, Who's There? Membership Inference on Aggregate Location Data Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro MIACV 111 270 0 21 Aug 2017
DeepSecure: Scalable Provably-Secure Deep Learning B. Rouhani M. Riazi F. Koushanfar FedML 52 415 0 24 May 2017
LOGAN: Membership Inference Attacks Against Generative Models Jamie Hayes Luca Melis G. Danezis Emiliano De Cristofaro 72 104 0 22 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,725 0 19 May 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 85 1,269 0 04 Apr 2017
Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective Seong Joon Oh Mario Fritz Bernt Schiele CVBM AAML 401 160 0 28 Mar 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 261 4,135 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 107 1,807 0 09 Sep 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 266 8,555 0 16 Aug 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks Nicolas Papernot Patrick McDaniel A. Swami Richard E. Harang AAML GAN SILM 51 456 0 28 Apr 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,678 0 08 Feb 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 112 3,962 0 24 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014