3 papers
S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
Pedro Miguel Sánchez Sánchez, Enrique Tomás MartÃnez 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 MartÃnez 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…