Web protection method based on URL self-learning

Abstract

The invention discloses a Web protection method based on URL self-learning, and the method comprises the steps: executing a corresponding preset action when a requested URL triggers a white list, carrying out the URL self-learning and Web safety protection synchronously in real time, and judging whether the requested URL exists in a memory database or not; if yes, transferring the request to a Webserver for response; and if not, loading and executing the self-learning strategy, and updating the self-learning strategy to the memory database. According to the method, URL self-learning and Web protection are synchronously carried out in real time, so that the real-time performance of a learning result is ensured. Learning results are stored in a memory database, the reading speed is high, and the protection efficiency is ensured. An effective period is set for a learning result, and data is cleared for re-learning after expiration, so that the effectiveness of the learning result is ensured, and the Web security protection efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of network security, in particular to a URL self-study-based Web protection method. Background technique [0002] According to survey statistics, most of the network attacks come from the application level rather than the network level, and more than half of the domestic sites have various security problems at the web level. Although most enterprises have deployed network security protection systems such as intrusion detection systems, network firewalls, and network antiviruses, many enterprises are still unable to cope with security threats from the Web application layer. [0003] Web Application Firewall is a security product that solves the security problems of Web applications. By means of security domain division and border isolation, a security barrier is strengthened between the client area and the server application system area. Through a series of security policy combinations, the maximum Protect t...

AI Technical Summary

Problems solved by technology

However, the current URL self-learning is mostly reviewing the daytime traffic data at night when the user access traffic is less, and it is not synchronized with the security protection, and the self-learning results are delayed.

On the other hand, the current database storage of self-learning results has a low reading rate; and the result data has been accumulated for a long time, and the validity is doubtful

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