Edge-Focused Temporal Graph Autoencoders for Anomalous Link Prediction in OT Networks

Anomalous Network Intrusion Detection Systems (NIDS) play a critical role in securing Operational Technology (OT) networks and can be used to detect novel/unknown attacks which traditional signature-based methods struggle with. Recent advancements in Graph Neural Networks (GNNs) have enabled new mac...

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Vydané v:	Proceedings (International Symposium on Digital Forensic and Security. Online) s. 1 - 6
Hlavní autori:	Howe, Alex, Papa, Mauricio
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 24.04.2025
Predmet:	Accuracy Autoencoders Digital forensics Feature extraction Graph convolutional networks Image edge detection Network intrusion detection Network security Real-time systems Telecommunication traffic
ISSN:	2768-1831
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