581 citations · 1k across the 25 of their papers we have counts for
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Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges
Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Pedro Miguel Sánchez Sánchez +5
In recent years, Federated Learning (FL) has gained relevance in training collaborative models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the mo…
A Lightweight Moving Target Defense Framework for Multi-purpose Malware Affecting IoT Devices
Jan von der Assen, Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez +4
Malware affecting Internet of Things (IoT) devices is rapidly growing due to the relevance of this paradigm in real-world scenarios. Specialized literature has also detected a tren…
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Timo Schenk +4
Device fingerprinting combined with Machine and Deep Learning (ML/DL) report promising performance when detecting cyberattacks targeting data managed by resource-constrained spectr…
CyberSpec: Intelligent Behavioral Fingerprinting to Detect Attacks on Crowdsensing Spectrum Sensors
Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez, Gérôme Bovet +2
Integrated sensing and communication (ISAC) is a novel paradigm using crowdsensing spectrum sensors to help with the management of spectrum scarcity. However, well-known vulnerabil…