Suppressing Poisoning Attacks on Federated Learning for Medical Imaging

15 July 2022

Papers citing "Suppressing Poisoning Attacks on Federated Learning for Medical Imaging"

5 / 5 papers shown

Title
Exploiting Supervised Poison Vulnerability to Strengthen Self-Supervised Defense Jeremy A. Styborski Mingzhi Lyu Y. Huang Adams Kong 42 0 0 13 Sep 2024
Predicting Infant Brain Connectivity with Federated Multi-Trajectory GNNs using Scarce Data Michalis Pistos Gang Li Weili Lin Dinggang Shen I. Rekik 20 0 0 01 Jan 2024
DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks Indu Joshi Priya Upadhya Gaurav Kumar Nayak Peter Schuffler Nassir Navab AAML FedML 38 0 0 14 Aug 2023
Federated Learning for Medical Image Analysis: A Survey Hao Guan Pew-Thian Yap Andrea Bozoki Mingxia Liu FedML OOD 37 114 0 09 Jun 2023
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018