Abstract: With valuable data constantly under attack, reactive security measures are no longer sufficient. Predicting cyber threats before they emerge is crucial. Cyberattacks do not occur randomly; ...

Abstract: To address the issue of limited topological generalization in Graph Attention Networks (GAT) due to the fixed hop range, this paper proposes a Random-K-Hop Graph Attention Network (RKGAT) to ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...