Research on Network Security Vulnerability Detection Method Based on Artificial Intelligence

Abstract

The Internet is gradually being used in various fields, and people’s lives are increasingly dependent on Internet technology. In network construction, we need to focus on maintaining network security and protecting the legitimate interests of users. In the network security defense system, network security vulnerability detection is an important part. Network attacks and network security vulnerability detection technology updates have shown a confrontational spiral in the field of network information security. One of the key contents of network security protection is how to effectively detect unknown network security vulnerabilities. In terms of network security vulnerability analysis, this paper studies cross-site scripting vulnerability analysis, SSL security vulnerability analysis, and binary vulnerability analysis; in terms of network security vulnerability prediction, it discusses random forest prediction models, convolutional neural network prediction models, and support vector machine predictions. Model; combined with common rules for network security vulnerability detection, comparative analysis of the network security vulnerability detection effects of several typical machine learning methods.