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20212025
most citedFedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2025

Chlorophyll-a Mapping and Prediction in the Mar Menor Lagoon Using C2RCC-Processed Sentinel 2 Imagery

Antonio Martínez-Ibarra, Aurora González-Vidal, Adrián Cánovas-Rodríguez +1

The Mar Menor, Europe's largest hypersaline coastal lagoon, located in southeastern Spain, has undergone severe eutrophication crises, with devastating impacts on biodiversity and…

cs.PF2025

Performance of Confidential Computing GPUs

Antonio Martínez Ibarra, Julian James Stephen, Aurora González Vidal +2

This work examines latency, throughput, and other metrics when performing inference on confidential GPUs. We explore different traffic patterns and scheduling strategies using a si…

cs.CY2024

Advancing Towards a Marine Digital Twin Platform: Modeling the Mar Menor Coastal Lagoon Ecosystem in the South Western Mediterranean

Yu Ye, Aurora González-Vidal, Alejandro Cisterna-García +3

Coastal marine ecosystems face mounting pressures from anthropogenic activities and climate change, necessitating advanced monitoring and modeling approaches for effective manageme…

cs.LG2024★ 1 cited

Federated Learning for Misbehaviour Detection with Variational Autoencoders and Gaussian Mixture Models

Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos +1

Federated Learning (FL) has become an attractive approach to collaboratively train Machine Learning (ML) models while data sources' privacy is still preserved. However, most of exi…

cs.LG2024★ 1 cited

FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning

Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos +1

Federated Learning (FL) represents a promising approach to typical privacy concerns associated with centralized Machine Learning (ML) deployments. Despite its well-known advantages…

cs.LG2021

Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges

Enrique Mármol Campos, Pablo Fernández Saura, Aurora González-Vidal +4

The application of Machine Learning (ML) techniques to the well-known intrusion detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks through…