Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,053 papers shown

Title
Towards Characterizing and Limiting Information Exposure in DNN Layers Fan Mo Ali Shahin Shamsabadi Kleomenis Katevas Andrea Cavallaro Hamed Haddadi 11 11 0 13 Jul 2019
On the Privacy Risks of Model Explanations Reza Shokri Martin Strobel Yair Zick MIACV PILM SILM FAtt 6 36 0 29 Jun 2019
DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM Bao Wang Quanquan Gu M. Boedihardjo Farzin Barekat Stanley J. Osher 16 25 0 28 Jun 2019
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference Klas Leino Matt Fredrikson MIACV 45 267 0 27 Jun 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 18 104 0 25 Jun 2019
The Cost of a Reductions Approach to Private Fair Optimization Daniel Alabi 41 3 0 23 Jun 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 40 2,160 0 21 Jun 2019
Efficient privacy preservation of big data for accurate data mining Pathum Chamikara Mahawaga Arachchige P. Bertók D. Liu S. Çamtepe I. Khalil 9 81 0 19 Jun 2019
Cloud-based Image Classification Service Is Not Robust To Simple Transformations: A Forgotten Battlefield Dou Goodman Tao Wei AAML 17 6 0 19 Jun 2019
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation Han Zhao Jianfeng Chi Yuan Tian Geoffrey J. Gordon MIACV 24 2 0 19 Jun 2019
Adversarial training approach for local data debiasing Ulrich Aïvodji F. Bidet Sébastien Gambs Rosin Claude Ngueveu Alain Tapp 11 7 0 19 Jun 2019
On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks Masoumeh Shafieinejad Jiaqi Wang Nils Lukas Xinda Li Florian Kerschbaum AAML 27 8 0 18 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer Virat Shejwalkar Amir Houmansadr 22 10 0 15 Jun 2019
Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks Felipe A. Mejia Paul Gamble Z. Hampel-Arias M. Lomnitz Nina Lopatina Lucas Tindall M. Barrios SILM 27 18 0 15 Jun 2019
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking Ziqi Yang Hung Dang E. Chang AAML 27 34 0 14 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 58 482 0 12 Jun 2019
Proposed Guidelines for the Responsible Use of Explainable Machine Learning Patrick Hall Navdeep Gill N. Schmidt SILM XAI FaML 11 28 0 08 Jun 2019
Reconstruction and Membership Inference Attacks against Generative Models Benjamin Hilprecht Martin Härterich Daniel Bernau AAML MIACV 21 185 0 07 Jun 2019
On Privacy Protection of Latent Dirichlet Allocation Model Training Fangyuan Zhao Xuebin Ren Shusen Yang Xinyu Yang 22 5 0 04 Jun 2019
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness Nhathai Phan Minh Nhat Vu Yang Liu R. Jin Dejing Dou Xintao Wu My T. Thai AAML 14 51 0 02 Jun 2019
Disparate Vulnerability to Membership Inference Attacks B. Kulynych Mohammad Yaghini Giovanni Cherubin Michael Veale Carmela Troncoso 13 39 0 02 Jun 2019
Bypassing Backdoor Detection Algorithms in Deep Learning T. Tan Reza Shokri FedML AAML 39 149 0 31 May 2019
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models Amrita Roy Chowdhury Theodoros Rekatsinas S. Jha 10 10 0 30 May 2019
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models S. K. Murakonda Reza Shokri George Theodorakopoulos MIACV 14 4 0 29 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 235 0 24 May 2019
The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services Yuantian Miao Minhui Xue Chao Chen Lei Pan Jinchao Zhang Benjamin Zi Hao Zhao Dali Kaafar Yang Xiang 19 34 0 17 May 2019
Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models Oren Melamud Chaitanya P. Shivade SyDa MedIm 13 35 0 16 May 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 30 331 0 09 May 2019
When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing Z. Luo Shangqing Zhao Zhuo Lu Jie Xu Y. Sagduyu AAML 17 53 0 04 May 2019
How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning Xinlei Pan Weiyao Wang Xiaoshuai Zhang Bo-wen Li Jinfeng Yi D. Song MIACV 69 26 0 24 Apr 2019
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning O. Gencoglu M. Gils E. Guldogan Chamin Morikawa Mehmet Süzen M. Gruber J. Leinonen H. Huttunen 11 36 0 16 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 19 35 0 12 Apr 2019
Membership Inference Attacks on Sequence-to-Sequence Models: Is My Data In Your Machine Translation System? Sorami Hisamoto Matt Post Kevin Duh MIACV SLR 30 106 0 11 Apr 2019
Private Hierarchical Clustering and Efficient Approximation Xianrui Meng D. Papadopoulos Alina Oprea Nikos Triandopoulos FedML 11 0 0 09 Apr 2019
Differentially Private Model Publishing for Deep Learning Lei Yu Ling Liu C. Pu Mehmet Emre Gursoy Stacey Truex FedML 15 264 0 03 Apr 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 17 250 0 01 Apr 2019
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 27 14 0 23 Mar 2019
Smart Home Personal Assistants: A Security and Privacy Review Jide S. Edu Jose Such Guillermo Suarez-Tangil 8 92 0 13 Mar 2019
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints Xing Hu Ling Liang Lei Deng Shuangchen Li Xinfeng Xie Yu Ji Yufei Ding Chang Liu T. Sherwood Yuan Xie AAML MLAU 21 36 0 10 Mar 2019
Copying Machine Learning Classifiers Irene Unceta Jordi Nin O. Pujol 14 18 0 05 Mar 2019
Attacking Graph-based Classification via Manipulating the Graph Structure Binghui Wang Neil Zhenqiang Gong AAML 33 154 0 01 Mar 2019
TamperNN: Efficient Tampering Detection of Deployed Neural Nets Erwan Le Merrer Gilles Tredan MLAU AAML 6 9 0 01 Mar 2019
High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions Xudong Sun Andrea Bommert Florian Pfisterer Jörg Rahnenführer Michel Lang B. Bischl FedML 16 12 0 24 Feb 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 15 7 0 24 Feb 2019
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment Ziqi Yang E. Chang Zhenkai Liang MLAU 33 60 0 22 Feb 2019
Measuring Membership Privacy on Aggregate Location Time-Series Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro 21 23 0 20 Feb 2019
XONN: XNOR-based Oblivious Deep Neural Network Inference M. Riazi Mohammad Samragh Hao Chen Kim Laine Kristin E. Lauter F. Koushanfar FedML GNN BDL 22 280 0 19 Feb 2019
Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets D. Froelicher J. Troncoso-Pastoriza João Sá Sousa Jean-Pierre Hubaux OOD SyDa 12 48 0 11 Feb 2019
On the security relevance of weights in deep learning Kathrin Grosse T. A. Trost Marius Mosbach Michael Backes Dietrich Klakow AAML 32 6 0 08 Feb 2019
Disguised-Nets: Image Disguising for Privacy-preserving Outsourced Deep Learning Sagar Sharma Keke Chen 13 1 0 05 Feb 2019