Yanxiang Hu

Semantic-guided edge enhancement for graph self-supervised learning in network intrusion detection.

To improve the discriminability of the network flow graph, a new node‑edge‑node attention algorithm is introduced for graph enhancement representation that integrates edge-aware attention and intra-edge feature self-attention collaboratively, thereby assists the model to perceive complex attack behaviors at multiple granular levels effectively.