2 citations · 4 across the 5 of their papers we have counts for
5 papers
Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning
Mario García-Márquez, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
Federated Learning (FL) has emerged as a key paradigm for building Trustworthy AI systems by enabling privacy-preserving, decentralized model training. However, FL is highly suscep…
From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0
Nuria Rodríguez-Barroso, Mario García-Márquez, M. Victoria Luzón +1
Federated Learning (FL) enables privacy-preserving collaborative learning, yet deployments increasingly show that privacy guarantees alone do not sustain trust in high-risk setting…
Improving -Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distance
Mario García-Márquez, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
The rapid development of artificial intelligence systems has amplified societal concerns regarding their usage, necessitating regulatory frameworks that encompass data privacy. Fed…
Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning
Mario García-Márquez, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
Federated Learning presents a nascent approach to machine learning, enabling collaborative model training across decentralized devices while safeguarding data privacy. However, its…
FLEX: FLEXible Federated Learning Framework
Francisco Herrera, Daniel Jiménez-López, Alberto Argente-Garrido +6
In the realm of Artificial Intelligence (AI), the need for privacy and security in data processing has become paramount. As AI applications continue to expand, the collection and h…