The analysis method of security vulnerability based on the knowledge graph

Abstract

Given the increasingly prominent network security issues, it is of great significance to deeply analyze the vulnerability of network space software and hardware resources. Although the existing Common Vulnerabilities and Exposures (CVE) security vulnerability database contains a wealth of vulnerability information, the information is poorly readable, the potential correlation is difficult to express intuitively, and the degree of visualization is insufficient. To solve the current problems, a method of constructing a knowledge graph of CVE security vulnerabilities is proposed. By acquiring raw data, ontology modeling, data extraction and import, the knowledge graph is imported into the Neo4j graph database to complete the construction of the CVE knowledge graph. Based on the knowledge graph, the in-depth analysis is performed from the cause dimension, time dimension and association dimension, and the results are displayed visually. Experiments show that this analysis method can intuitively and effectively mine the intrinsic value of CVE security vulnerability data.