2 citations · 3 across the 4 of their papers we have counts for
4 papers
S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Chao Feng +3
Decentralized Federated Learning (DFL) enables collaborative, privacy-preserving model training without relying on a central server. This decentralized approach reduces bottlenecks…
ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes
Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Miguel Fernández Llamas +3
Decentralized Federated Learning (DFL) trains models in a collaborative and privacy-preserving manner while removing model centralization risks and improving communication bottlene…
Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Gérôme Bovet +1
In the current cybersecurity landscape, protecting military devices such as communication and battlefield management systems against sophisticated cyber attacks is crucial. Malware…
A Big Data Architecture for Early Identification and Categorization of Dark Web Sites
Javier Pastor-Galindo, Hông-Ân Sandlin, Félix Gómez Mármol +2
The dark web has become notorious for its association with illicit activities and there is a growing need for systems to automate the monitoring of this space. This paper proposes…