collaborators

6 papers

cs.AI2026

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…

cs.CR2026

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…

cs.CR2025

RAB-DEF: Dynamic and explainable defense against adversarial attacks in Federated Learning to fair poor clients

Nuria Rodríguez-Barroso, M. Victoria Luzón, Francisco Herrera

At the same time that artificial intelligence is becoming popular, concern and the need for regulation is growing, including among other requirements the data privacy. In this cont…

cs.LG2025

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…

cs.CR2025

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…

cs.LG2025

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…