Modelling and Quantifying Membership Information Leakage in Machine
Learning

Modelling and Quantifying Membership Information Leakage in Machine Learning

29 January 2020

Papers citing "Modelling and Quantifying Membership Information Leakage in Machine Learning"

10 / 10 papers shown

Title
Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting Berend Gort Xiao-Yang Liu Xinghang Sun Jiechao Gao Shuai Chen Chris Wang 32 13 0 12 Sep 2022
Towards Sparsified Federated Neuroimaging Models via Weight Pruning Dimitris Stripelis Umang Gupta Nikhil J. Dhinagar Greg Ver Steeg Paul M. Thompson J. Ambite FedML 29 0 0 24 Aug 2022
On the Privacy Properties of GAN-generated Samples Zinan Lin Vyas Sekar Giulia Fanti PICV 24 26 0 03 Jun 2022
Investigation of Alternative Measures for Mutual Information Bulut Kuskonmaz Jaron Skovsted Gundersen R. Wisniewski 24 4 0 02 Feb 2022
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 27 233 0 18 Nov 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models Benjamin Zi Hao Zhao Aviral Agrawal Catisha Coburn Hassan Jameel Asghar Raghav Bhaskar M. Kâafar Darren Webb Peter Dickinson MIACV 31 38 0 12 Mar 2021
Revisiting Membership Inference Under Realistic Assumptions Bargav Jayaraman Lingxiao Wang Katherine Knipmeyer Quanquan Gu David Evans 24 147 0 21 May 2020
Disparate Vulnerability to Membership Inference Attacks B. Kulynych Mohammad Yaghini Giovanni Cherubin Michael Veale Carmela Troncoso 15 39 0 02 Jun 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 21 34 0 17 May 2019