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 PDF HTML

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

50 / 465 papers shown

Title
Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods William Paul Yinzhi Cao Miaomiao Zhang Philippe Burlina AAML MedIm 26 15 0 04 Mar 2021
DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing Wenxiao Wang Tianhao Wang Lun Wang Nanqing Luo Pan Zhou D. Song R. Jia 8 16 0 02 Mar 2021
Differential Privacy and Byzantine Resilience in SGD: Do They Add Up? R. Guerraoui Nirupam Gupta Rafael Pinot Sébastien Rouault John Stephan 33 30 0 16 Feb 2021
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey Yuantian Miao Chao Chen Lei Pan Qing-Long Han Jun Zhang Yang Xiang AAML 51 68 0 16 Feb 2021
Membership Inference Attacks are Easier on Difficult Problems Avital Shafran Shmuel Peleg Yedid Hoshen MIACV 19 16 0 15 Feb 2021
Node-Level Membership Inference Attacks Against Graph Neural Networks Xinlei He Rui Wen Yixin Wu Michael Backes Yun Shen Yang Zhang 21 93 0 10 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 21 51 0 08 Feb 2021
On Utility and Privacy in Synthetic Genomic Data Bristena Oprisanu Georgi Ganev Emiliano De Cristofaro 22 13 0 05 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
Membership Inference Attack on Graph Neural Networks Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 40 97 0 17 Jan 2021
Training Data Leakage Analysis in Language Models Huseyin A. Inan Osman Ramadan Lukas Wutschitz Daniel Jones Victor Rühle James Withers Robert Sim MIACV PILM 37 9 0 14 Jan 2021
Model Extraction and Defenses on Generative Adversarial Networks Hailong Hu Jun Pang SILM MIACV 31 14 0 06 Jan 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
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Mohamed Bennai Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 81 100 0 04 Jan 2021
Federated Unlearning Gaoyang Liu Xiaoqiang Ma Yang Yang Chen Wang Jiangchuan Liu MU 43 53 0 27 Dec 2020
FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism Jiasi Weng Jian Weng Hongwei Huang Chengjun Cai Cong Wang FedML 19 28 0 19 Dec 2020
TransMIA: Membership Inference Attacks Using Transfer Shadow Training Seira Hidano Takao Murakami Yusuke Kawamoto MIACV 30 13 0 30 Nov 2020
Use the Spear as a Shield: A Novel Adversarial Example based Privacy-Preserving Technique against Membership Inference Attacks Mingfu Xue Chengxiang Yuan Can He Zhiyu Wu Yushu Zhang Zhe Liu Weiqiang Liu MIACV 6 12 0 27 Nov 2020
When Machine Learning Meets Privacy: A Survey and Outlook B. Liu Ming Ding Sina shaham W. Rahayu F. Farokhi Zihuai Lin 20 282 0 24 Nov 2020
Synthetic Data -- Anonymisation Groundhog Day Theresa Stadler Bristena Oprisanu Carmela Troncoso 18 156 0 13 Nov 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 33 109 0 07 Nov 2020
FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries Seng Pei Liew Tsubasa Takahashi MIACV FedML 28 9 0 27 Oct 2020
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity Analysis Xudong Pan Mi Zhang Yifan Yan Jiaming Zhu Zhemin Yang AAML 13 21 0 26 Oct 2020
A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric Zekun Xu Abhinav Aggarwal Oluwaseyi Feyisetan Nathanael Teissier 19 55 0 22 Oct 2020
Feature Inference Attack on Model Predictions in Vertical Federated Learning Xinjian Luo Yuncheng Wu Xiaokui Xiao Beng Chin Ooi FedML AAML 11 219 0 20 Oct 2020
Image Obfuscation for Privacy-Preserving Machine Learning Mathilde Raynal R. Achanta Mathias Humbert 38 13 0 20 Oct 2020
Security and Privacy Considerations for Machine Learning Models Deployed in the Government and Public Sector (white paper) Nader Sehatbakhsh E. Daw O. Savas Amin Hassanzadeh I. Mcculloh SILM 14 1 0 12 Oct 2020
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks A. Salem Michael Backes Yang Zhang 8 35 0 07 Oct 2020
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning Vasisht Duddu A. Boutet Virat Shejwalkar GNN 24 4 0 02 Oct 2020
Quantifying Privacy Leakage in Graph Embedding Vasisht Duddu A. Boutet Virat Shejwalkar MIACV 17 119 0 02 Oct 2020
On Primes, Log-Loss Scores and (No) Privacy Abhinav Aggarwal Zekun Xu Oluwaseyi Feyisetan Nathanael Teissier MIACV 8 0 0 17 Sep 2020
Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning Yang Zou Zhikun Zhang Michael Backes Yang Zhang MIACV 17 32 0 10 Sep 2020
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning Mohammad Naseri Jamie Hayes Emiliano De Cristofaro FedML 33 144 0 08 Sep 2020
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning Cen Chen Bingzhe Wu Minghui Qiu Li Wang Jun Zhou PILM 16 10 0 04 Sep 2020
Enclave-Aware Compartmentalization and Secure Sharing with Sirius Zahra Tarkhani Anil Madhavapeddy 6 2 0 03 Sep 2020
Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries Shadi Rahimian Tribhuvanesh Orekondy Mario Fritz MIACV 13 25 0 01 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
Not one but many Tradeoffs: Privacy Vs. Utility in Differentially Private Machine Learning Benjamin Zi Hao Zhao M. Kâafar N. Kourtellis 13 26 0 20 Aug 2020
Data Minimization for GDPR Compliance in Machine Learning Models Abigail Goldsteen Gilad Ezov Ron Shmelkin Micha Moffie Ariel Farkash 8 63 0 06 Aug 2020
The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures Evgenios M. Kornaropoulos Silei Ren R. Tamassia AAML 16 17 0 01 Aug 2020
Membership Leakage in Label-Only Exposures Zheng Li Yang Zhang 34 237 0 30 Jul 2020
Label-Only Membership Inference Attacks Christopher A. Choquette-Choo Florian Tramèr Nicholas Carlini Nicolas Papernot MIACV MIALM 35 494 0 28 Jul 2020
Anonymizing Machine Learning Models Abigail Goldsteen Gilad Ezov Ron Shmelkin Micha Moffie Ariel Farkash MIACV 19 5 0 26 Jul 2020
How Does Data Augmentation Affect Privacy in Machine Learning? Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu MU 26 1 0 21 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 39 213 0 15 Jul 2020
Sharing Models or Coresets: A Study based on Membership Inference Attack Hanlin Lu Changchang Liu T. He Shiqiang Wang Kevin S. Chan MIACV FedML 19 15 0 06 Jul 2020
Reducing Risk of Model Inversion Using Privacy-Guided Training Abigail Goldsteen Gilad Ezov Ariel Farkash 30 4 0 29 Jun 2020
On the Effectiveness of Regularization Against Membership Inference Attacks Yigitcan Kaya Sanghyun Hong Tudor Dumitras 40 27 0 09 Jun 2020
Sponge Examples: Energy-Latency Attacks on Neural Networks Ilia Shumailov Yiren Zhao Daniel Bates Nicolas Papernot Robert D. Mullins Ross J. Anderson SILM 19 127 0 05 Jun 2020
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements Xiaoyi Chen A. Salem Dingfan Chen Michael Backes Shiqing Ma Qingni Shen Zhonghai Wu Yang Zhang SILM 29 228 0 01 Jun 2020