activity
20172025
most citedClustered Federated Learning Architecture for Network Anomaly Detection in Large Scale Heterogeneous IoT Networks

139 citations · 228 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2025

Privacy-Preserving Feature Valuation in Vertical Federated Learning Using Shapley-CMI and PSI Permutation

Unai Laskurain, Aitor Aguirre-Ortuzar, Urko Zurutuza

Federated Learning (FL) is an emerging machine learning paradigm that enables multiple parties to collaboratively train models without sharing raw data, ensuring data privacy. In V…

cs.CR2023★ 139 cited

Clustered Federated Learning Architecture for Network Anomaly Detection in Large Scale Heterogeneous IoT Networks

Xabier Sáez-de-Cámara, Jose Luis Flores, Cristóbal Arellano +2

There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover, the sophistication and motivation of those attacks is increasing. The vast scale of IoT…

cs.CR2022★ 37 cited

Gotham Testbed: a Reproducible IoT Testbed for Security Experiments and Dataset Generation

Xabier Sáez-de-Cámara, Jose Luis Flores, Cristóbal Arellano +2

The growing adoption of the Internet of Things (IoT) has brought a significant increase in attacks targeting those devices. Machine learning (ML) methods have shown promising resul…

cs.LG2020★ 17 cited

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect

Oscar Serradilla, Ekhi Zugasti, Urko Zurutuza

Given the growing amount of industrial data spaces worldwide, deep learning solutions have become popular for predictive maintenance, which monitor assets to optimise maintenance t…

eess.SP2019★ 29 cited

Optimising maintenance: What are the expectations for Cyber Physical Systems

Erkki Jantunen, Urko Zurutuza, Luis Lino Ferreira +1

The need for maintenance is based on the wear of components of machinery. If this need can be defined reliably beforehand so that no unpredicted failures take place then the mainte…

cs.CR2017★ 6 cited

On the Feasibility of Distinguishing Between Process Disturbances and Intrusions in Process Control Systems Using Multivariate Statistical Process Control

Mikel Iturbe, José Camacho, Iñaki Garitano +2

Process Control Systems (PCSs) are the operating core of Critical Infrastructures (CIs). As such, anomaly detection has been an active research field to ensure CI normal operation.…