arXiv Machine Learning June 9, 2026 By Laura Jiang, Reza Ryan, Qian Li, Nasim Ferdosian

A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection

Read the original on arXiv Machine Learning →

arXiv:2510. 26307v3 Announce Type: replace-cross Abstract: Anomaly detection is a critical task in cybersecurity, where identifying insider threats, access violations, and coordinated attacks is essential for ensuring system resilience.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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