Research on computer network link vulnerability detection based on knowledge graph technology
The vulnerability information of computer network links has the characteristics of complex types,broad sources and large quantities,which makes it particularly difficult to determine the threat of such vulnerabilities.Knowledge graph technology has the characteristics of data integration and unified representation,so it can unify and structurally integrate complex vulnerability information.Therefore,a computer network link vulnerability detection method based on knowledge graph technology is proposed.Various data source vulnerability information of computer network links is collected,vulnerability entity knowledge and relationship knowledge are extracted,and a network link vulnerability knowledge graph is constructed.A convolutional neural network(CNN)model is used to learn the vulnerability knowledge in the constructed knowledge graph,and the network link vulnerability detection is implemented by the trained model.The results show that the method can be used to construct a vulnerability knowledge graph for working conditions containing different types and quantities of link vulnerabilities.In addition,the accuracy of vulnerability threat detection always remains above 90%.It indicates that the detection results of the detection method studied are accurate and reliable,so the method studied can provide guarantees for the secure transmission of data in computer network links.
万方数据
维普
