Large-Scale Mean-Field Federated Learning for Detection and Defense: A Byzantine Robustness Approach in IoT
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3409610
Abstract: Federated learning (FL) protects data privacy by sharing gradients across clients rather than local training data. However, malicious clients (e.g., attackers and stragglers) hiding in large-scale FL will severely reduce the learning performance. Thus, how… read more here.
Keywords: large scale; mean field; byzantine robustness; field ... See more keywords
Auditable Federated Learning With Byzantine Robustness
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Computational Social Systems"
DOI: 10.1109/tcss.2023.3266019
Abstract: Machine learning (ML) has led to disruptive innovations in many fields, such as medical diagnoses. A key enabler for ML is large training data, but existing data, such as medical data, are not fully exploited… read more here.
Keywords: byzantine robustness; privacy; client; federated learning ... See more keywords