82 citations · 88 across the 3 of their papers we have counts for
3 papers
Fedstellar: A Platform for Decentralized Federated Learning
Enrique Tomás Martínez Beltrán, Ángel Luis Perales Gómez, Chao Feng +6
In 2016, Google proposed Federated Learning (FL) as a novel paradigm to train Machine Learning (ML) models across the participants of a federation while preserving data privacy. Si…
FederatedTrust: A Solution for Trustworthy Federated Learning
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Ning Xie +3
The rapid expansion of the Internet of Things (IoT) and Edge Computing has presented challenges for centralized Machine and Deep Learning (ML/DL) methods due to the presence of dis…
Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Gérôme Bovet +1
In the last years, the number of IoT devices deployed has suffered an undoubted explosion, reaching the scale of billions. However, some new cybersecurity issues have appeared toge…