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Federated Explainability for Network Anomaly Characterization
(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 ...
On the use of MiniCPS for conducting rigorous security experiments in Software-Defined Industrial Control Systems
(Springer, 2024)
Software-Defined Networking (SDN) offers a global view over the network and the ability of centrally and dynamically managing network flows, making them ideal for creating security threat detection and mitigation solutions. ...
Deobfuscating leetspeak with deep learning to improve spam filtering
(UNIR - Universidad Internacional de La Rioja, 2023)
The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are ...