Abstract: With the increasing number of cyber threats, the knowledge graph construction technology of threat intelligence has become an important research direction in the field of network security. However, the current knowledge graph construction technology lacks the speed and accuracy of knowledge acquisition. In view of these problems, this paper proposes a supervised deep learning model, which automatically extracts the entity and entity relationship of threat intelligence, and visualizes the knowledge map through graph data. The experimental results show that the method based on the deep learning model for threat intelligence entities and entities extraction has a great improvement in accuracy, which provides a powerful guarantee for the automated construction of threat intelligence knowledge graph.

Key words: threat intelligence, entity extraction, deep learning, knowledge graph