Our paper: 'FLgym: Towards Robust and Byzantine-Resilient Federated Learning' has been accepted in IEEE Transactions on Information Forensics & Security!
Published: 30 September 2025
Our paper: 'FLgym: Towards Robust and Byzantine-Resilient Federated Learning' has been accepted in IEEE Transactions on Information Forensics & Security! Great work by Ke Xiao, Qiyuan Wang, and Christos Anagnostopoulos.
The FLgym paradigm is about a two-stage framework for Byzantine-resilient FL that integrates three components: a model similarity-based detection mechanism, a validation mechanism based on similarity estimation of clients’ local data, and a weight recovery mechanism for identified Byzantine clients.
First published: 30 September 2025