Computer Network Vulnerability Detection and Semantic Data Analysis Optimization Based on Artificial Intelligence

Abstract

In order to solve the network security vulnerabilities in the process of network information interaction, which affect the integrity and confidentiality of data. The computer network vulnerability detection and semantic data analysis optimization based on artificial intelligence are proposed, and the results show that the final accuracy of the test set is improved to 88.5%, but the false positive rate is as high as 18%. Based on the direct classification model, the code under test is compared with the vulnerability template, the model fuses the two direct classification models and reduces the false positive rate to less than 5% under the condition that the accuracy is basically the same.