Membership Inference Attacks on Deep Regression Models for Neuroimaging

6 May 2021

Papers citing "Membership Inference Attacks on Deep Regression Models for Neuroimaging"

20 / 20 papers shown

Title
Generating Synthetic Data with Formal Privacy Guarantees: State of the Art and the Road Ahead Viktor Schlegel Anil A Bharath Zilong Zhao Kevin Yee 66 0 0 26 Mar 2025
Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study Eric Aubinais Philippe Formont Pablo Piantanida Elisabeth Gassiat 38 0 0 10 Feb 2025
Membership Inference Attacks and Defenses in Federated Learning: A Survey Li Bai Haibo Hu Qingqing Ye Haoyang Li Leixia Wang Jianliang Xu FedML 69 13 0 09 Dec 2024
Inference Attacks: A Taxonomy, Survey, and Promising Directions Feng Wu Lei Cui Shaowen Yao Shui Yu 39 2 0 04 Jun 2024
Privacy Threats in Stable Diffusion Models Thomas Cilloni Charles Fleming Charles Walter 22 3 0 15 Nov 2023
Fundamental Limits of Membership Inference Attacks on Machine Learning Models Eric Aubinais Elisabeth Gassiat Pablo Piantanida MIACV 43 2 0 20 Oct 2023
Federated Learning over Harmonized Data Silos Dimitris Stripelis J. Ambite FedML 15 2 0 15 May 2023
Single-round Self-supervised Distributed Learning using Vision Transformer Sangjoon Park Ik-jae Lee Jun Won Kim Jong Chul Ye FedML MedIm 11 1 0 05 Jan 2023
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey Huiyun Cao Wenlong Zou Yinkun Wang Ting Song Mengjun Liu AAML 35 4 0 19 Oct 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 19 0 0 24 Aug 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 25 74 0 17 May 2022
Secure & Private Federated Neuroimaging Dimitris Stripelis Umang Gupta Hamza Saleem Nikhil J. Dhinagar Tanmay Ghai ... Greg Ver Steeg Srivatsan Ravi Muhammad Naveed Paul M. Thompson J. Ambite FedML OOD 11 2 0 11 May 2022
Multi-Task Distributed Learning using Vision Transformer with Random Patch Permutation Sangjoon Park Jong Chul Ye FedML MedIm 22 19 0 07 Apr 2022
Adaptive Differentially Private Empirical Risk Minimization Xiaoxia Wu Lingxiao Wang Irina Cristali Quanquan Gu Rebecca Willett 24 6 0 14 Oct 2021
Information-theoretic generalization bounds for black-box learning algorithms Hrayr Harutyunyan Maxim Raginsky Greg Ver Steeg Aram Galstyan 32 41 0 04 Oct 2021
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption Dimitris Stripelis Hamza Saleem Tanmay Ghai Nikhil J. Dhinagar Umang Gupta ... Greg Ver Steeg Srivatsan Ravi Muhammad Naveed Paul M. Thompson J. Ambite FedML 44 53 0 07 Aug 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 28 408 0 14 Mar 2021
Scaling Neuroscience Research using Federated Learning Dimitris Stripelis J. Ambite Pradeep Lam Paul M. Thompson FedML 37 28 0 16 Feb 2021
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 185 358 0 24 Mar 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,698 0 18 Mar 2020