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
NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-Sourced Datasets Runhua Xu J. Joshi Chao Li FedML 29 18 0 18 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 27 4 0 18 Dec 2020
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design Jun Zhou Longfei Zheng Chaochao Chen Yan Wang Xiaolin Zheng Bingzhe Wu Cen Chen Li Wang Jianwei Yin FedML 38 3 0 17 Dec 2020
Confidential Machine Learning on Untrusted Platforms: A Survey Sagar Sharma Keke Chen FedML 22 15 0 15 Dec 2020
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 32 13 0 14 Dec 2020
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges Kashif Ahmad Majdi Maabreh M. Ghaly Khalil Khan Junaid Qadir Ala I. Al-Fuqaha 32 142 0 14 Dec 2020
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 295 1,833 0 14 Dec 2020
Privacy-preserving Decentralized Aggregation for Federated Learning Beomyeol Jeon S. Ferdous Muntasir Raihan Rahman A. Walid FedML 33 52 0 13 Dec 2020
Addressing Visual Search in Open and Closed Set Settings Nathan G. Drenkow Philippe Burlina Neil Fendley Kachi Odoemene Jared Markowitz ObjD 24 0 0 11 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? Gavin Brown Mark Bun Vitaly Feldman Adam D. Smith Kunal Talwar 253 93 0 11 Dec 2020
TARA: Training and Representation Alteration for AI Fairness and Domain Generalization William Paul Armin Hadzic Neil J. Joshi F. Alajaji Philippe Burlina 31 19 0 11 Dec 2020
Communication-Computation Efficient Secure Aggregation for Federated Learning Beongjun Choi Jy-yong Sohn Dong-Jun Han Jaekyun Moon FedML 20 89 0 10 Dec 2020
Privacy Amplification by Decentralization Edwige Cyffers A. Bellet FedML 54 39 0 09 Dec 2020
Risk Management Framework for Machine Learning Security J. Breier A. Baldwin H. Balinsky Yang Liu AAML 16 3 0 09 Dec 2020
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective Jingwei Sun Ang Li Binghui Wang Huanrui Yang Hai Li Yiran Chen FedML 27 164 0 08 Dec 2020
Class Clown: Data Redaction in Machine Unlearning at Enterprise Scale Daniel L. Felps Amelia D. Schwickerath Joyce D. Williams Trung N. Vuong Alan Briggs M. Hunt Evan Sakmar David D. Saranchak Tyler Shumaker AILaw 28 12 0 08 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 357 0 07 Dec 2020
Privacy-Preserving Synthetic Smart Meters Data Ganesh Del Grosso Georg Pichler Pablo Piantanida 28 4 0 06 Dec 2020
Unleashing the Tiger: Inference Attacks on Split Learning Dario Pasquini G. Ateniese M. Bernaschi FedML 39 148 0 04 Dec 2020
MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent K.R. Jayaram Archit Verma A. Verma Gegi Thomas Colin Sutcher-Shepard FedML 11 11 0 01 Dec 2020
TransMIA: Membership Inference Attacks Using Transfer Shadow Training Seira Hidano Takao Murakami Yusuke Kawamoto MIACV 33 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 8 12 0 27 Nov 2020
Advancements of federated learning towards privacy preservation: from federated learning to split learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe FedML 29 82 0 25 Nov 2020
When Machine Learning Meets Privacy: A Survey and Outlook B. Liu Ming Ding Sina shaham W. Rahayu F. Farokhi Zihuai Lin 25 282 0 24 Nov 2020
Challenges in Deploying Machine Learning: a Survey of Case Studies Andrei Paleyes Raoul-Gabriel Urma Neil D. Lawrence 28 389 0 18 Nov 2020
Bootstrap Aggregation for Point-based Generalized Membership Inference Attacks Daniel L. Felps Amelia D. Schwickerath Joyce D. Williams Trung N. Vuong Alan Briggs M. Hunt Evan Sakmar David D. Saranchak Tyler Shumaker MIACV 6 1 0 17 Nov 2020
A Theoretical Perspective on Differentially Private Federated Multi-task Learning Huiwen Wu Cen Chen Li Wang FedML 16 12 0 14 Nov 2020
Synthetic Data -- Anonymisation Groundhog Day Theresa Stadler Bristena Oprisanu Carmela Troncoso 21 156 0 13 Nov 2020
Golden Grain: Building a Secure and Decentralized Model Marketplace for MLaaS Jiasi Weng Jian Weng Chengjun Cai Hongwei Huang Cong Wang AI4TS 24 21 0 12 Nov 2020
Revisiting Secure Computation Using Functional Encryption: Opportunities and Research Directions Runhua Xu J. Joshi 9 5 0 12 Nov 2020
Privacy Preservation in Federated Learning: An insightful survey from the GDPR Perspective N. Truong Kai Sun Siyao Wang Florian Guitton Yike Guo FedML 20 9 0 10 Nov 2020
Privacy-Preserving XGBoost Inference Xianrui Meng J. Feigenbaum 17 14 0 09 Nov 2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds T. Tony Cai Yichen Wang Linjun Zhang FedML 43 20 0 08 Nov 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 38 110 0 07 Nov 2020
Bayes Security: A Not So Average Metric K. Chatzikokolakis Giovanni Cherubin C. Palamidessi Carmela Troncoso 19 14 0 06 Nov 2020
Deep-Dup: An Adversarial Weight Duplication Attack Framework to Crush Deep Neural Network in Multi-Tenant FPGA Adnan Siraj Rakin Yukui Luo Xiaolin Xu Deliang Fan AAML 25 49 0 05 Nov 2020
Trustworthy AI Richa Singh Mayank Vatsa Nalini Ratha 23 4 0 02 Nov 2020
Monitoring-based Differential Privacy Mechanism Against Query-Flooding Parameter Duplication Attack Haonan Yan Xiaoguang Li Hui Li Jiamin Li Wenhai Sun Fenghua Li AAML 26 1 0 01 Nov 2020
Evaluation of Inference Attack Models for Deep Learning on Medical Data Maoqiang Wu Xinyue Zhang Jiahao Ding H. Nguyen Rong Yu Miao Pan Stephen T. C. Wong MIACV 20 18 0 31 Oct 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
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes Jinyuan Jia Binghui Wang Neil Zhenqiang Gong AAML 35 5 0 26 Oct 2020
Speaker Anonymization with Distribution-Preserving X-Vector Generation for the VoicePrivacy Challenge 2020 H.C.M. Turner Giulio Lovisotto Ivan Martinovic 16 21 0 26 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
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization Bang Wu Xiangwen Yang Shirui Pan Xingliang Yuan MIACV MLAU 55 53 0 24 Oct 2020
Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq Chuan Xu Giovanni Neglia Richard Vidal FedML 67 85 0 23 Oct 2020
Investigating Membership Inference Attacks under Data Dependencies Thomas Humphries Simon Oya Lindsey Tulloch Matthew Rafuse I. Goldberg Urs Hengartner Florian Kerschbaum MIACV MIALM 30 35 0 23 Oct 2020
A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric Zekun Xu Abhinav Aggarwal Oluwaseyi Feyisetan Nathanael Teissier 21 55 0 22 Oct 2020
DPD-InfoGAN: Differentially Private Distributed InfoGAN Vaikkunth Mugunthan V. Gokul Lalana Kagal Shlomo Dubnov 24 10 0 22 Oct 2020
Amnesiac Machine Learning Laura Graves Vineel Nagisetty Vijay Ganesh MU MIACV 27 248 0 21 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