Webpage security monitoring method, computer program product, equipment and storage medium
By analyzing the dynamic content and user behavior of web pages using a pre-trained analysis model trained by machine learning, identifying and preventing attacks such as XSS and SQL injection, the problems of high false positive rates and poor user experience in the existing technology are solved, and more efficient and accurate web page security monitoring is achieved.
CN119760717AActive Publication Date: 2025-04-04BEIJING TOPSEC NETWORK SECURITY TECH +2
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Patent Information
- Application Number
- CN202411846063.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-13
- Publication Date
- 2025-04-04
- Estimated Expiration
- 2044-12-13
AI Technical Summary
Technical Problem
Existing page security protection methods cannot effectively protect against cross-site scripting attacks (XSS) and SQL injection, and the false positive rate is high, resulting in poor user experience.
Method used
Machine learning is used to train a predetermined analysis model, and analyze it by obtaining the dynamic content data of the web page and user behavior data, identifying potential malicious code and abnormal patterns, and implementing response measures according to the predetermined security policy.
Benefits of technology
It significantly improves the accuracy of web security monitoring, reduces false alarm rates, improves user experience, and provides a safer network environment.
✦ Generated by Eureka AI based on patent content.
Abstract
The embodiment of the invention provides a webpage security monitoring method, a computer program product, equipment and a storage medium. The method comprises the following steps: acquiring dynamic content data and user behavior data of a webpage; inputting into a trained predetermined analysis model to obtain an analysis result; under the condition that the analysis result indicates that the security problem exists, executing a predetermined response measure according to a predetermined security policy; the predetermined analysis model comprises the following training processes: obtaining dynamic content data and user behavior data of a webpage in a predetermined time period; performing first predetermined analysis on the dynamic content data to obtain a first analysis result data set; performing second predetermined analysis on the user behavior data based on a predetermined pattern recognition algorithm to obtain a second analysis result data set; and inputting the first analysis result data set and the second analysis result data set into a predetermined analysis model for machine learning to obtain a trained predetermined analysis model.
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