294 citations · 352 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
Addressing Data Quality Decompensation in Federated Learning via Dynamic Client Selection
Qinjun Fei, Nuria Rodríguez-Barroso, María Victoria Luzón +2
In cross-silo Federated Learning (FL), client selection is critical to ensure high model performance, yet it remains challenging due to data quality decompensation, budget constrai…
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…
Membership Inference Attacks fueled by Few-Short Learning to detect privacy leakage tackling data integrity
Daniel Jiménez-López, Nuria Rodríguez-Barroso, M. Victoria Luzón +1
Deep learning models have an intrinsic privacy issue as they memorize parts of their training data, creating a privacy leakage. Membership Inference Attacks (MIA) exploit it to obt…
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…