Graph Neural Networks for Threat Intelligence and Cyber-Attack Path Prediction
Graph Neural Networks (GNNs) have become a potent paradigm of complex data related to relations, and it is especially applicable to threat intelligence analysis and prediction of cyber-attack lines. The proposed paper describes a GNN framework that combines the sources of heterogeneous cyber threat intelligence, includ...