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ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models

4 February 2021

Michael Backes

Emiliano De Cristofaro

Mario Fritz

Yang Zhang

AAML

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Papers citing "ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models"

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Title
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 105 6 0 22 Oct 2024
Membership Inference Attacks Against Recommender Systems Minxing Zhang Zhaochun Ren Zihan Wang Pengjie Ren Zhumin Chen Pengfei Hu Yang Zhang MIACV AAML 69 88 0 16 Sep 2021
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning Hongbin Liu Jinyuan Jia Wenjie Qu Neil Zhenqiang Gong 39 99 0 25 Aug 2021
BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning Jinyuan Jia Yupei Liu Neil Zhenqiang Gong SILM SSL 104 160 0 01 Aug 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 77 52 0 08 Feb 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 139 226 0 11 Jan 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown Basel Alomair Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 509 1,953 0 14 Dec 2020
Membership Leakage in Label-Only Exposures Zheng Li Yang Zhang 80 246 0 30 Jul 2020
ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning S. K. Murakonda Reza Shokri 47 76 0 18 Jul 2020
An Overview of Privacy in Machine Learning Emiliano De Cristofaro SILM 65 86 0 18 May 2020
When Machine Unlearning Jeopardizes Privacy Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 88 232 0 05 May 2020
Information Leakage in Embedding Models Congzheng Song A. Raghunathan MIACV 70 271 0 31 Mar 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 355 375 0 24 Mar 2020
Analyzing and Improving the Image Quality of StyleGAN Tero Karras S. Laine M. Aittala Janne Hellsten J. Lehtinen Timo Aila GAN 321 5,829 0 03 Dec 2019
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks Yuheng Zhang R. Jia Hengzhi Pei Wenxiao Wang Yue Liu Basel Alomair AAML 113 422 0 17 Nov 2019
Thieves on Sesame Street! Model Extraction of BERT-based APIs Kalpesh Krishna Gaurav Singh Tomar Ankur P. Parikh Nicolas Papernot Mohit Iyyer MIACV MLAU 114 201 0 27 Oct 2019
Detecting AI Trojans Using Meta Neural Analysis Xiaojun Xu Qi Wang Huichen Li Nikita Borisov Carl A. Gunter Yue Liu 88 325 0 08 Oct 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 76 394 0 23 Sep 2019
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference Alexandre Sablayrolles Matthijs Douze Yann Ollivier Cordelia Schmid Hervé Jégou MIACV 76 368 0 29 Aug 2019
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference Klas Leino Matt Fredrikson MIACV 96 272 0 27 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer Virat Shejwalkar Amir Houmansadr 61 10 0 15 Jun 2019
Reconstruction and Membership Inference Attacks against Generative Models Benjamin Hilprecht Martin Härterich Daniel Bernau AAML MIACV 70 191 0 07 Jun 2019
Overlearning Reveals Sensitive Attributes Congzheng Song Vitaly Shmatikov 53 156 0 28 May 2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 78 257 0 01 Apr 2019
Knockoff Nets: Stealing Functionality of Black-Box Models Tribhuvanesh Orekondy Bernt Schiele Mario Fritz MLAU 108 537 0 06 Dec 2018
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 52 474 0 16 Jul 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 102 950 0 04 Jun 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 157 1,482 0 10 May 2018
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks Nicholas Carlini Chang-rui Liu Ulfar Erlingsson Jernej Kos Basel Alomair 153 1,149 0 22 Feb 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 149 466 0 14 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 96 939 0 09 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,926 0 25 Aug 2017
LOGAN: Membership Inference Attacks Against Generative Models Jamie Hayes Luca Melis G. Danezis Emiliano De Cristofaro 81 104 0 22 May 2017
Age Progression/Regression by Conditional Adversarial Autoencoder Zhifei Zhang Yang Song Hairong Qi GAN CVBM 87 1,119 0 27 Feb 2017
Towards the Science of Security and Privacy in Machine Learning Nicolas Papernot Patrick McDaniel Arunesh Sinha Michael P. Wellman AAML 96 474 0 11 Nov 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 278 4,160 0 18 Oct 2016
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data Nicolas Papernot Martín Abadi Ulfar Erlingsson Ian Goodfellow Kunal Talwar 94 1,020 0 18 Oct 2016
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 1.4K 14,608 0 07 Oct 2016
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library Nicolas Papernot Fartash Faghri Nicholas Carlini Ian Goodfellow Reuben Feinman ... David Berthelot P. Hendricks Jonas Rauber Rujun Long Patrick McDaniel AAML 83 514 0 03 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 109 1,811 0 09 Sep 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,162 0 01 Jul 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 92 840 0 06 May 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,682 0 08 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,510 0 10 Dec 2015
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 271 14,027 0 19 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 116 3,076 0 14 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,733 0 09 Mar 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,429 0 28 Nov 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,529 0 04 Sep 2014
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers G. Ateniese G. Felici L. Mancini A. Spognardi Antonio Villani Domenico Vitali 87 463 0 19 Jun 2013