Systematic Evaluation of Privacy Risks of Machine Learning Models

24 March 2020

Papers citing "Systematic Evaluation of Privacy Risks of Machine Learning Models"

36 / 36 papers shown

Title
Unveiling Impact of Frequency Components on Membership Inference Attacks for Diffusion Models Puwei Lian Yujun Cai Songze Li 36 0 0 27 May 2025
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis Ruijun Deng Zhihui Lu Qiang Duan FedML 85 0 0 14 Apr 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study Ayana Moshruba Ihsen Alouani Maryam Parsa AAML 66 3 0 24 Feb 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 87 34 0 20 Jan 2025
Trustworthiness of Stochastic Gradient Descent in Distributed Learning Hongyang Li Caesar Wu Mohammed Chadli Said Mammar Pascal Bouvry 66 1 0 28 Oct 2024
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 47 4 0 22 Oct 2024
Adversarial Attacks on Data Attribution Xinhe Wang Pingbang Hu Junwei Deng Jiaqi W. Ma TDI 82 0 0 09 Sep 2024
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher Alessio Mora Lorenzo Valerio Paolo Bellavista A. Passarella FedML MU 68 2 0 14 Aug 2024
AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI Kaveen Hiniduma Suren Byna J. L. Bez Ravi Madduri 62 7 0 27 Jun 2024
Convolutional Networks with Dense Connectivity Gao Huang Zhuang Liu Geoff Pleiss Laurens van der Maaten Kilian Q. Weinberger 3DV 46 443 0 08 Jan 2020
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 48 386 0 23 Sep 2019
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models Dingfan Chen Ning Yu Yang Zhang Mario Fritz 25 52 0 09 Sep 2019
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Bingzhe Wu Shiwan Zhao Chaochao Chen Haoyang Xu Li Wang Xiaolu Zhang Guangyu Sun Jun Zhou 30 45 0 21 Aug 2019
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference Klas Leino Matt Fredrikson MIACV 65 268 0 27 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer Virat Shejwalkar Amir Houmansadr 29 10 0 15 Jun 2019
Reconstruction and Membership Inference Attacks against Generative Models Benjamin Hilprecht Martin Härterich Daniel Bernau AAML MIACV 25 186 0 07 Jun 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 21 237 0 24 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 35 250 0 01 Apr 2019
Machine Learning with Membership Privacy using Adversarial Regularization Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV 30 468 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 72 935 0 04 Jun 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 115 1,461 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 105 1,128 0 22 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 24 224 0 13 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 149 3,171 0 01 Feb 2018
Machine Learning Models that Remember Too Much Congzheng Song Thomas Ristenpart Vitaly Shmatikov VLM 45 508 0 22 Sep 2017
Knock Knock, Who's There? Membership Inference on Aggregate Location Data Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro MIACV 84 269 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 188 11,962 0 19 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 92 1,851 0 20 May 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 95 1,385 0 24 Feb 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 194 4,075 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 45 1,009 0 18 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 568 36,599 0 25 Aug 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 138 6,049 0 01 Jul 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 219 7,951 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.1K 192,638 0 10 Dec 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 709 99,991 0 04 Sep 2014