Zerrendatu honen arabera: egilea "Arellano, Cristóbal"
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Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
Zurutuza, Urko (Elsevier, 2023)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, diverse hardware and software, and being ... -
Federated Explainability for Network Anomaly Characterization
Zurutuza, Urko (ACM, 2023)Machine learning (ML) based systems have shown promising results for intrusion detection due to their ability to learn complex patterns. In particular, unsupervised anomaly detection approaches offer practical advantages ... -
Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generation
Sáez-de-Cámara, Xabier; Zurutuza, Urko (IEEE, 2023)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 results for intrusion detection; however, the ... -
Leveraging Digital Twins and SIEM Integration for Incident Response in OT Environments
Zurutuza, Urko (Universidad de Sevilla, 2024)The Industrial Internet of Things (IIoT) has digitally transformed industrial processes albeit at the expense of increasing exposure to new security threats. System Information and Event Management (SIEM) systems, typically ...
