AI RESEARCH
AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders
arXiv CS.LG
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ArXi:2511.17113v2 Announce Type: replace-cross Network Intrusion Detection Systems (NIDS) are essential tools for detecting network attacks and intrusions. While extensive research has explored the use of supervised Machine Learning for attack detection and characterisation, these methods require accurately labelled datasets, which are very costly to obtain. Moreover, existing public datasets have limited and/or outdated attacks, and many of them suffer from mislabelled data.