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XGA-E: an explainability-enhanced graph neural network for network traffic anomaly detection

Abstract Graph neural network (GNN) have demonstrated excellent performance in network traffic anomaly detection research. However, existing GNN-based approaches often lack interpretability, and their detection performance remains to be improved. To address these challenges, we propose XGA-E, an int...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Min Yang, Caiming Liu
Format: Artigo
Sprache:Inglês
Veröffentlicht: SpringerOpen 2026-01-01
Schriftenreihe:Cybersecurity
Schlagworte:
Network Traffic
Anomaly Detection
Graph Neural Network
Explainability-Enhanced
Edge Embedding
Online-Zugang:https://doi.org/10.1186/s42400-025-00487-x
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