MaGOS-IDS: A Mahalanobis-Enhanced OpenMax Method for Graph Neural Network-Based Intrusion Detection
MaGOS-IDS is proposed, which extracts topology-aware embeddings with an edge-aware GCN that fuses flow-level edge features directly into message passing, whitens each class with a regularized Mahalanobis distance so the reject decision respects per-class variance and correlation, and calibrates a per-class EVT tail on...