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
Image Obfuscation for Privacy-Preserving Machine Learning Mathilde Raynal R. Achanta Mathias Humbert 38 13 0 20 Oct 2020
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians Ishaq Aden-Ali H. Ashtiani Gautam Kamath 46 42 0 19 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 681 0 19 Oct 2020
From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And Security Sheng Shen Tianqing Zhu Di Wu Wei Wang Wanlei Zhou FedML OOD 23 77 0 19 Oct 2020
Unexpected Information Leakage of Differential Privacy Due to Linear Property of Queries Wen Huang Shijie Zhou Yongjian Liao MIACV 8 6 0 18 Oct 2020
Layer-wise Characterization of Latent Information Leakage in Federated Learning Fan Mo Anastasia Borovykh Mohammad Malekzadeh Hamed Haddadi Soteris Demetriou FedML 25 31 0 17 Oct 2020
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings Vinith Suriyakumar Nicolas Papernot Anna Goldenberg Marzyeh Ghassemi OOD 36 64 0 13 Oct 2020
Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications David Byrd Antigoni Polychroniadou FedML 6 150 0 12 Oct 2020
A Comprehensive Survey on Local Differential Privacy Toward Data Statistics and Analysis Teng Wang Xuefeng Zhang Xuefeng Zhang Xinyu Yang 22 86 0 11 Oct 2020
Voting-based Approaches For Differentially Private Federated Learning Yuqing Zhu Xiang Yu Yi-Hsuan Tsai Francesco Pittaluga M. Faraki Manmohan Chandraker Yu Wang FedML 29 21 0 09 Oct 2020
Latent Dirichlet Allocation Model Training with Differential Privacy Fangyuan Zhao Xuebin Ren Shusen Yang Qing Han Peng Zhao Xinyu Yang 33 28 0 09 Oct 2020
Knowledge-Enriched Distributional Model Inversion Attacks Si-An Chen Mostafa Kahla R. Jia Guo-Jun Qi 24 93 0 08 Oct 2020
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks A. Salem Michael Backes Yang Zhang 10 35 0 07 Oct 2020
Can we Generalize and Distribute Private Representation Learning? Sheikh Shams Azam Taejin Kim Seyyedali Hosseinalipour Carlee Joe-Wong S. Bagchi Christopher G. Brinton 44 10 0 05 Oct 2020
Towards Bidirectional Protection in Federated Learning Lun Wang Qi Pang Shuai Wang D. Song FedML 27 3 0 02 Oct 2020
Practical One-Shot Federated Learning for Cross-Silo Setting Qinbin Li Bingsheng He D. Song FedML 24 114 0 02 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
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 29 57 0 02 Oct 2020
Oblivious Sampling Algorithms for Private Data Analysis Sajin Sasy O. Ohrimenko FedML 14 16 0 28 Sep 2020
Information Obfuscation of Graph Neural Networks Peiyuan Liao Han Zhao Keyulu Xu Tommi Jaakkola Geoffrey J. Gordon Stefanie Jegelka Ruslan Salakhutdinov AAML 23 34 0 28 Sep 2020
STAN: Synthetic Network Traffic Generation with Generative Neural Models Shengzhe Xu Manish Marwah M. Arlitt Naren Ramakrishnan DiffM AI4TS 30 27 0 27 Sep 2020
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning S. Kadhe Nived Rajaraman O. O. Koyluoglu Kannan Ramchandran FedML 38 159 0 23 Sep 2020
Training Production Language Models without Memorizing User Data Swaroop Indra Ramaswamy Om Thakkar Rajiv Mathews Galen Andrew H. B. McMahan Franccoise Beaufays FedML 25 92 0 21 Sep 2020
Learning Realistic Patterns from Unrealistic Stimuli: Generalization and Data Anonymization K. Nikolaidis Stein Kristiansen T. Plagemann V. Goebel Knut Liestøl ... G. Traaen Britt Overland Harriet Akre L. Aakerøy S. Steinshamn 8 4 0 21 Sep 2020
On Primes, Log-Loss Scores and (No) Privacy Abhinav Aggarwal Zekun Xu Oluwaseyi Feyisetan Nathanael Teissier MIACV 10 0 0 17 Sep 2020
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare Matei Grama M. Mușat Luis Muñoz-González Jonathan Passerat-Palmbach Daniel Rueckert A. Alansary OOD FedML 25 45 0 17 Sep 2020
An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks Sumit Kumar Jha Susmit Jha Rickard Ewetz Sunny Raj Alvaro Velasquez L. Pullum A. Swami MIACV 14 8 0 17 Sep 2020
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models Yixi Xu Soumendu Sundar Mukherjee Xiyang Liu Shruti Tople Rahul Dodhia J. L. Ferres MIACV 27 11 0 11 Sep 2020
Quantifying Membership Inference Vulnerability via Generalization Gap and Other Model Metrics Jason Bentley Daniel Gibney Gary Hoppenworth Sumit Kumar Jha MIACV 9 16 0 11 Sep 2020
Trading Data For Learning: Incentive Mechanism For On-Device Federated Learning Rui Hu Yanmin Gong FedML 28 63 0 11 Sep 2020
Accelerating 2PC-based ML with Limited Trusted Hardware M. Nawaz Aditya Gulati Kunlong Liu Vishwajeet Agrawal P. Ananth Trinabh Gupta 11 2 0 11 Sep 2020
Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing William J. Buchanan Muhammad Ali Imran M. Rehman Lei Zhang Q. Abbasi C. Chrysoulas D. Haynes Nikolaos Pitropakis Pavlos Papadopoulos 8 14 0 10 Sep 2020
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy Tom Farrand Fatemehsadat Mireshghallah Sahib Singh Andrew Trask FedML 11 88 0 10 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
Attribute Privacy: Framework and Mechanisms Wanrong Zhang O. Ohrimenko Rachel Cummings 18 36 0 08 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 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
Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping Jaewoo Lee Daniel Kifer 6 55 0 07 Sep 2020
A Framework for Private Matrix Analysis Jalaj Upadhyay Sarvagya Upadhyay 32 4 0 06 Sep 2020
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning Cen Chen Bingzhe Wu Minghui Qiu Li Wang Jun Zhou PILM 22 10 0 04 Sep 2020
Enclave-Aware Compartmentalization and Secure Sharing with Sirius Zahra Tarkhani Anil Madhavapeddy 14 2 0 03 Sep 2020
Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries Shadi Rahimian Tribhuvanesh Orekondy Mario Fritz MIACV 19 25 0 01 Sep 2020
POSEIDON: Privacy-Preserving Federated Neural Network Learning Sinem Sav Apostolos Pyrgelis J. Troncoso-Pastoriza D. Froelicher Jean-Philippe Bossuat João Sá Sousa Jean-Pierre Hubaux FedML 19 153 0 01 Sep 2020
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model S. Hahn Junghye Lee FedML 11 2 0 29 Aug 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 25 48 0 28 Aug 2020
Measurement-driven Security Analysis of Imperceptible Impersonation Attacks Shasha Li K. Khalil Yikang Shen Chengyu Song S. Krishnamurthy Amit K. Roy-Chowdhury A. Swami AAML 22 2 0 26 Aug 2020
Vulnerability of Face Recognition Systems Against Composite Face Reconstruction Attack Hadi Mansourifar W. Shi AAML CVBM 11 2 0 23 Aug 2020
On the Intrinsic Differential Privacy of Bagging Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong FedML SILM 74 8 0 22 Aug 2020
Not one but many Tradeoffs: Privacy Vs. Utility in Differentially Private Machine Learning Benjamin Zi Hao Zhao M. Kâafar N. Kourtellis 15 26 0 20 Aug 2020