Construct a Network Security Vulnerability Knowledge Graph Based on HPO-BiLSTM-CRF

In order to solve the problems of scattered vulnerability information and weak correlation in current vulnerability analysis technology, this paper proposes a method based on HPO-BiLSTM-CRF, which uses the unique relational data structure of the knowledge graph to provide the ability to analyze problems from a relational perspective. Method for constructing network security vulnerability knowledge graph. Based on the public vulnerability data collected from relevant databases in the field of cyberspace security, an optimized bidirectional long short-term memory network and conditional random field fusion model HPO-BiLSTM-CRF was constructed to realize knowledge extraction and store the results in the Neo4j graph database. Comparative experimental results show that the knowledge graph construction method based on HPO-BiLSTM-CRF proposed in this article has the advantages of high efficiency and high accuracy.