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20212025
most citedRL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT

21 citations · 51 across the 5 of their papers we have counts for

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4 papers · 1 filter

cs.CR2025

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…

cs.CR2022★ 21 cited

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…

cs.CR2021★ 10 cited

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…

cs.CR2021★ 18 cited

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…