Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,056 papers shown

Title
Privacy Leakage Avoidance with Switching Ensembles R. Izmailov Peter Lin Chris Mesterharm S. Basu 25 2 0 18 Nov 2019
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data Xinyun Chen Wenxiao Wang Chris Bender Yiming Ding R. Jia Bo-wen Li D. Song AAML 27 107 0 17 Nov 2019
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks Yuheng Zhang R. Jia Hengzhi Pei Wenxiao Wang Bo-wen Li D. Song AAML 48 410 0 17 Nov 2019
Defending Against Model Stealing Attacks with Adaptive Misinformation Sanjay Kariyappa Moinuddin K. Qureshi MLAU AAML 14 106 0 16 Nov 2019
Federated and Differentially Private Learning for Electronic Health Records Stephen R. Pfohl Andrew M. Dai Katherine A. Heller OOD FedML 26 49 0 13 Nov 2019
CHEETAH: An Ultra-Fast, Approximation-Free, and Privacy-Preserved Neural Network Framework based on Joint Obscure Linear and Nonlinear Computations Qiao Zhang Cong Wang Chunsheng Xin Hongyi Wu 13 4 0 12 Nov 2019
Privacy-Preserving Gradient Boosting Decision Trees Yue Liu Zhaomin Wu Zeyi Wen Bingsheng He 19 77 0 11 Nov 2019
Theoretical Guarantees for Model Auditing with Finite Adversaries Mario Díaz Peter Kairouz Jiachun Liao Lalitha Sankar MLAU AAML 34 2 0 08 Nov 2019
Collaborative Machine Learning Markets with Data-Replication-Robust Payments O. Ohrimenko Shruti Tople Sebastian Tschiatschek OOD FedML 9 24 0 08 Nov 2019
Coverage Guided Testing for Recurrent Neural Networks Wei Huang Youcheng Sun Xing-E. Zhao James Sharp Wenjie Ruan Jie Meng Xiaowei Huang AAML 33 47 0 05 Nov 2019
Relations among different privacy notions Jun Zhao 13 1 0 02 Nov 2019
Reducing audio membership inference attack accuracy to chance: 4 defenses M. Lomnitz Nina Lopatina Paul Gamble Z. Hampel-Arias Lucas Tindall Felipe A. Mejia M. Barrios AAML 17 0 0 31 Oct 2019
Quantifying (Hyper) Parameter Leakage in Machine Learning Vasisht Duddu D. V. Rao AAML MIACV FedML 36 5 0 31 Oct 2019
Fault Tolerance of Neural Networks in Adversarial Settings Vasisht Duddu N. Pillai D. V. Rao V. Balas SILM AAML 27 11 0 30 Oct 2019
Efficient Privacy-Preserving Stochastic Nonconvex Optimization Lingxiao Wang Bargav Jayaraman David Evans Quanquan Gu 19 28 0 30 Oct 2019
Secure and Efficient Federated Transfer Learning Shreya Sharma C. Xing Yang Liu Yan Kang FedML 11 77 0 29 Oct 2019
MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection Anuj Dubey Rosario Cammarota Aydin Aysu AAML 24 78 0 29 Oct 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 36 194 0 27 Oct 2019
Towards Distributed Privacy-Preserving Prediction Lingjuan Lyu Yee Wei Law K. S. Ng Shibei Xue Jun Zhao Mengmeng Yang Lei Liu FedML 21 4 0 25 Oct 2019
Weighted Distributed Differential Privacy ERM: Convex and Non-convex Yilin Kang Yong Liu Weiping Wang 15 10 0 23 Oct 2019
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text Oluwaseyi Feyisetan Tom Diethe Thomas Drake 29 74 0 20 Oct 2019
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations Oluwaseyi Feyisetan Borja Balle Thomas Drake Tom Diethe 12 151 0 20 Oct 2019
Federated Generative Privacy Aleksei Triastcyn Boi Faltings FedML 16 63 0 18 Oct 2019
Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey Bin Qian Jie Su Z. Wen D. N. Jha Yinhao Li ... Albert Y. Zomaya Omer F. Rana Lizhe Wang Maciej Koutny R. Ranjan 28 4 0 11 Oct 2019
Membership Model Inversion Attacks for Deep Networks S. Basu R. Izmailov Chris Mesterharm MIACV 15 13 0 09 Oct 2019
Detecting AI Trojans Using Meta Neural Analysis Xiaojun Xu Qi Wang Huichen Li Nikita Borisov Carl A. Gunter Bo-wen Li 31 321 0 08 Oct 2019
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics Abeer Alshehri Chaochao Chen Shiwan Zhao Cen Chen Yuan Yao Guangyu Sun L. Sonenberg Xiaolu Zhang Jun Zhou BDL 14 21 0 05 Oct 2019
Sampling Unknown Decision Functions to Build Classifier Copies Irene Unceta Diego Palacios Jordi Nin O. Pujol 14 8 0 01 Oct 2019
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions Zinan Lin Alankar Jain Chen Wang Giulia Fanti Vyas Sekar 28 22 0 30 Sep 2019
Robust Membership Encoding: Inference Attacks and Copyright Protection for Deep Learning Congzheng Song Reza Shokri MIACV 18 5 0 27 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 24 18 0 27 Sep 2019
Alleviating Privacy Attacks via Causal Learning Shruti Tople Amit Sharma A. Nori MIACV OOD 33 32 0 27 Sep 2019
GAMIN: An Adversarial Approach to Black-Box Model Inversion Ulrich Aïvodji Sébastien Gambs Timon Ther MLAU 27 42 0 26 Sep 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 24 384 0 23 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments Alesia Chernikova Alina Oprea AAML 19 35 0 23 Sep 2019
From Server-Based to Client-Based Machine Learning: A Comprehensive Survey Renjie Gu Chaoyue Niu Fan Wu Guihai Chen Chun Hu Chengfei Lyu Zhihua Wu 30 25 0 18 Sep 2019
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges Jinyuan Jia Neil Zhenqiang Gong AAML SILM 15 16 0 17 Sep 2019
VeriML: Enabling Integrity Assurances and Fair Payments for Machine Learning as a Service Lingchen Zhao Qian Wang Cong Wang Qi Li Chao Shen Xiaodong Lin Bo Feng Minxin Du VLM 13 86 0 16 Sep 2019
Differentially Private Meta-Learning Jeffrey Li M. Khodak S. Caldas Ameet Talwalkar FedML 35 106 0 12 Sep 2019
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models Dingfan Chen Ning Yu Yang Zhang Mario Fritz 23 52 0 09 Sep 2019
Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization Shaofeng Li Minhui Xue Benjamin Zi Hao Zhao Haojin Zhu Dali Kaafar 16 59 0 06 Sep 2019
Duet: An Expressive Higher-order Language and Linear Type System for Statically Enforcing Differential Privacy Joseph P. Near David Darais Chiké Abuah Tim Stevens Pranav Gaddamadugu ... Neel Somani Mu Zhang Nikhil Sharma Alex Shan D. Song 21 37 0 05 Sep 2019
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform Mathias Lécuyer Riley Spahn Kiran Vodrahalli Roxana Geambasu Daniel J. Hsu 16 44 0 04 Sep 2019
High Accuracy and High Fidelity Extraction of Neural Networks Matthew Jagielski Nicholas Carlini David Berthelot Alexey Kurakin Nicolas Papernot MLAU MIACV 39 372 0 03 Sep 2019
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference Alexandre Sablayrolles Matthijs Douze Yann Ollivier Cordelia Schmid Hervé Jégou MIACV 31 352 0 29 Aug 2019
On Inferring Training Data Attributes in Machine Learning Models Benjamin Zi Hao Zhao Hassan Jameel Asghar Raghav Bhaskar M. Kâafar TDI MIACV 20 11 0 28 Aug 2019
Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis Jing Ma Qiuchen Zhang Jian Lou Joyce C. Ho Li Xiong Xiaoqian Jiang 30 44 0 26 Aug 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
Security in Brain-Computer Interfaces: State-of-the-art, opportunities, and future challenges Sergio López Bernal Alberto Huertas Celdrán Gregorio Martínez Pérez Michael Taynnan Barros Sasitharan Balasubramaniam 9 13 0 09 Aug 2019
That which we call private Ulfar Erlingsson Ilya Mironov A. Raghunathan Shuang Song 13 26 0 08 Aug 2019