21 citations · 51 across the 5 of their papers we have counts for
5 papers
A Crowdsensing Intrusion Detection Dataset For Decentralized Federated Learning Models
Chao Feng, Alberto Huertas Celdran, Jing Han +6
This paper introduces a dataset and an experimental study on Decentralized Federated Learning (DFL) for Internet of Things (IoT) crowdsensing malware detection. The dataset compris…
RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT
Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez, Jan von der Assen +4
Cybercriminals are moving towards zero-day attacks affecting resource-constrained devices such as single-board computers (SBC). Assuming that perfect security is unrealistic, Movin…
Studying Drowsiness Detection Performance while Driving through Scalable Machine Learning Models using Electroencephalography
José Manuel Hidalgo Rogel, Enrique Tomás Martínez Beltrán, Mario Quiles Pérez +3
- Background / Introduction: Driver drowsiness is a significant concern and one of the leading causes of traffic accidents. Advances in cognitive neuroscience and computer science…
Robust Federated Learning for execution time-based device model identification under label-flipping attack
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, José Rafael Buendía Rubio +2
The computing device deployment explosion experienced in recent years, motivated by the advances of technologies such as Internet-of-Things (IoT) and 5G, has led to a global scenar…
A methodology to identify identical single-board computers based on hardware behavior fingerprinting
Pedro Miguel Sánchez Sánchez, José María Jorquera Valero, Alberto Huertas Celdrán +3
The connectivity and resource-constrained nature of single-board devices open the door to cybersecurity concerns affecting Internet of Things (IoT) scenarios. One of the most impor…