Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,058 papers shown

Title
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification Dominique Mercier Adriano Lucieri Mohsin Munir Andreas Dengel Sheraz Ahmed 21 11 0 29 Nov 2021
Machine unlearning via GAN Kongyang Chen Yao Huang Yiwen Wang MU 27 7 0 22 Nov 2021
Backdoor Attack through Frequency Domain Tong Wang Yuan Yao Feng Xu Shengwei An Yangqiu Song Ting Wang AAML 29 33 0 22 Nov 2021
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 29 233 0 18 Nov 2021
How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN R. Thomas McCoy P. Smolensky Tal Linzen Jianfeng Gao Asli Celikyilmaz SyDa 32 119 0 18 Nov 2021
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 18 103 0 17 Nov 2021
To Trust or Not To Trust Prediction Scores for Membership Inference Attacks Dominik Hintersdorf Lukas Struppek Kristian Kersting 26 14 0 17 Nov 2021
Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud Jonathan Will Onur Arslan Jonathan Bader Dominik Scheinert L. Thamsen 32 4 0 15 Nov 2021
On the Importance of Difficulty Calibration in Membership Inference Attacks Lauren Watson Chuan Guo Graham Cormode Alex Sablayrolles 31 120 0 15 Nov 2021
Property Inference Attacks Against GANs Junhao Zhou Yufei Chen Chao Shen Yang Zhang AAML MIACV 35 52 0 15 Nov 2021
Eluding Secure Aggregation in Federated Learning via Model Inconsistency Dario Pasquini Danilo Francati G. Ateniese FedML 28 101 0 14 Nov 2021
Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities Esma Mansouri-Benssassi Simon Rogers Jim Q. Smith F. Ritchie E. Jefferson 27 5 0 10 Nov 2021
Lightweight machine unlearning in neural network Kongyang Chen Yiwen Wang Yao Huang MU 30 7 0 10 Nov 2021
Membership Inference Attacks Against Self-supervised Speech Models Wei-Cheng Tseng Wei-Tsung Kao Hung-yi Lee 43 14 0 09 Nov 2021
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection Shubhankar Mohapatra Sajin Sasy Xi He Gautam Kamath Om Thakkar 114 32 0 09 Nov 2021
Get a Model! Model Hijacking Attack Against Machine Learning Models A. Salem Michael Backes Yang Zhang AAML 30 28 0 08 Nov 2021
Reconstructing Training Data from Diverse ML Models by Ensemble Inversion Qian Wang Daniel Kurz 20 9 0 05 Nov 2021
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups A. Wainakh Ephraim Zimmer Sandeep Subedi Jens Keim Tim Grube Shankar Karuppayah Alejandro Sánchez Guinea Max Mühlhäuser 27 9 0 05 Nov 2021
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 56 9 0 05 Nov 2021
Secure Machine Learning in the Cloud Using One Way Scrambling by Deconvolution Yiftach Savransky Roni Mateless Gilad Katz 11 0 0 04 Nov 2021
3-D PET Image Generation with tumour masks using TGAN R. V. Bergen Jean-Francois Rajotte F. Yousefirizi I. Klyuzhin Arman Rahmim R. Ng MedIm 27 7 0 02 Nov 2021
Revealing and Protecting Labels in Distributed Training Trung D. Q. Dang Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Peter Chin Franccoise Beaufays 20 26 0 31 Oct 2021
Efficient passive membership inference attack in federated learning Oualid Zari Chuan Xu Giovanni Neglia FedML 6 34 0 31 Oct 2021
Optimizing Secure Decision Tree Inference Outsourcing Yifeng Zheng Cong Wang Ruochen Wang Huayi Duan Surya Nepal 21 6 0 31 Oct 2021
Backdoor Pre-trained Models Can Transfer to All Lujia Shen S. Ji Xuhong Zhang Jinfeng Li Jing Chen Jie Shi Chengfang Fang Jianwei Yin Ting Wang AAML SILM 41 120 0 30 Oct 2021
10 Security and Privacy Problems in Large Foundation Models Jinyuan Jia Hongbin Liu Neil Zhenqiang Gong 19 7 0 28 Oct 2021
Federated Learning with Heterogeneous Differential Privacy Nasser Aldaghri Hessam Mahdavifar Ahmad Beirami FedML 35 2 0 28 Oct 2021
Gradient Inversion with Generative Image Prior Jinwoo Jeon Jaechang Kim Kangwook Lee Sewoong Oh Jungseul Ok 30 148 0 28 Oct 2021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges Mohammadreza Salehi Hossein Mirzaei Dan Hendrycks Yixuan Li M. Rohban Mohammad Sabokrou OOD 38 191 0 26 Oct 2021
CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning Zhensu Sun Xiaoning Du Fu Song Mingze Ni Li Li 36 68 0 25 Oct 2021
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning Anvith Thudi Hengrui Jia Ilia Shumailov Nicolas Papernot MU 13 142 0 22 Oct 2021
Federated Unlearning via Class-Discriminative Pruning Junxiao Wang Song Guo Xin Xie Heng Qi MU 13 137 0 22 Oct 2021
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 39 14 0 22 Oct 2021
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes Chonghua Liao Jiafan He Quanquan Gu 29 17 0 19 Oct 2021
Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications Bang Wu Xiangwen Yang Shirui Pan Xingliang Yuan AAML 21 60 0 17 Oct 2021
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy Anda Cheng Jiaxing Wang Xi Sheryl Zhang Qiang Chen Peisong Wang Jian Cheng 39 27 0 16 Oct 2021
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture Xinyu Tang Saeed Mahloujifar Liwei Song Virat Shejwalkar Milad Nasr Amir Houmansadr Prateek Mittal 27 75 0 15 Oct 2021
Adaptive Differentially Private Empirical Risk Minimization Xiaoxia Wu Lingxiao Wang Irina Cristali Quanquan Gu Rebecca Willett 45 6 0 14 Oct 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 351 0 13 Oct 2021
On the Security Risks of AutoML Ren Pang Zhaohan Xi S. Ji Xiapu Luo Ting Wang AAML 27 10 0 12 Oct 2021
Sharing FANCI Features: A Privacy Analysis of Feature Extraction for DGA Detection Benedikt Holmes Arthur Drichel Ulrike Meyer 34 1 0 12 Oct 2021
Generalization Techniques Empirically Outperform Differential Privacy against Membership Inference Jiaxiang Liu Simon Oya Florian Kerschbaum MIACV 22 9 0 11 Oct 2021
Continual Learning with Differential Privacy Pradnya Desai Phung Lai Nhathai Phan My T. Thai 32 7 0 11 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 135 120 0 07 Oct 2021
Federated Learning from Small Datasets Michael Kamp Jonas Fischer Jilles Vreeken FedML 32 26 0 07 Oct 2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models Divyat Mahajan Shruti Tople Amit Sharma OOD 21 7 0 07 Oct 2021
On the Privacy Risks of Deploying Recurrent Neural Networks in Machine Learning Models Yunhao Yang Parham Gohari Ufuk Topcu AAML 35 3 0 06 Oct 2021
How BPE Affects Memorization in Transformers Eugene Kharitonov Marco Baroni Dieuwke Hupkes 180 32 0 06 Oct 2021
Inference Attacks Against Graph Neural Networks Zhikun Zhang Min Chen Michael Backes Yun Shen Yang Zhang MIACV AAML GNN 33 50 0 06 Oct 2021
Information-theoretic generalization bounds for black-box learning algorithms Hrayr Harutyunyan Maxim Raginsky Greg Ver Steeg Aram Galstyan 50 41 0 04 Oct 2021