Detecting Anomalies Using Graph Neural Networks: A Review
Sena Ozgunay, Louise Travé-Massuyès, Jean–Michel Loubes, Sena Ferreira, Raul · HAL (Le Centre pour la Communication Scientifique Directe) · 2025
Anomaly detection is the process of identifying unusual behaviors in systems. In this wide-ranging field, graph neural networks (GNNs) are highly effective compared to the other proposed approaches in the literature. This article summarizes the representative GNN-based methods for anomaly detection and proposes a novel taxonomy based on how these methods predict anomalies.