Network-Level Adversaries in Federated Learning

27 August 2022

Papers citing "Network-Level Adversaries in Federated Learning"

7 / 7 papers shown

Title
SureFED: Robust Federated Learning via Uncertainty-Aware Inward and Outward Inspection Nasimeh Heydaribeni Ruisi Zhang T. Javidi Cristina Nita-Rotaru F. Koushanfar FedML 55 0 0 04 Aug 2023
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses M. Ferrag Othmane Friha B. Kantarci Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Djallel Hamouda Muna Al-Hawawreh K. Choo 25 43 0 17 Jun 2023
Poisoning Attacks in Federated Edge Learning for Digital Twin 6G-enabled IoTs: An Anticipatory Study M. Ferrag B. Kantarci Lucas C. Cordeiro Merouane Debbah K. Choo AAML 13 5 0 21 Mar 2023
Can Decentralized Learning be more robust than Federated Learning? Mathilde Raynal Dario Pasquini Carmela Troncoso OOD FedML 38 4 0 07 Mar 2023
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning Md Tamjid Hossain Shafkat Islam S. Badsha Haoting Shen AAML 55 41 0 21 Sep 2021
Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering Jian Xu Shao-Lun Huang Linqi Song Tian-Shing Lan FedML AAML 37 42 0 13 Sep 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 611 0 27 Dec 2020