Research on Optimization of Web Vulnerability Automatic Detection Technology Based on Semantic Recognition
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Yonggang Li, Min Han, Aiyi Cao, Shanmin Pan
In recent years, with the rapid development of China's energy internet, the era of the Internet of Everything is coming. Coupled with the wide application of Web2.0, traditional client applications can no longer meet the increasing demand for network interconnection, and Web applications have gradually become mainstream. New web application security issues are becoming more and more prominent. Different web applications also have different vulnerabilities, which will be discovered by criminals and may be used maliciously. Especially in the era of energy internet, the fall of a system often threatens the overall energy security. In order to discover vulnerabilities in time and propose solutions, Web vulnerability automatic detection technology is also increasingly important. In response to the above problems, this paper proposes the optimization research of automatic vulnerability detection technology based on semantic recognition, applies the semantic recognition technology to the Web automatic detection technology and proposes a variety of optimization strategies, so as to obtain more comprehensive and accurate vulnerability information of Web applications. Improve the overall coverage and accuracy of web system vulnerability detection.
Web vulnerability, cross-site scripting, semantic recognition, automatic detection, optimization strategy