The Design And Implementation Of Website Content Security Monitoring System

As the general public has officially entered the network environment,the importance of website security has become increasingly prominent.While netizens are focused on cyber attacks,they have failed to focus on content-based security issues.The security problem based on content belongs to the security filtering of semantics,which belongs to the level that directly affects the public.Therefore,to carry out corresponding analysis work on this issue is a very critical research project.The thesis focuses on the defects of the detection scheme based on rule base matching.At the same time,it integrates solutions such as split word restoration and homophone matching,so as to effectively solve the defects of the old plan that can not effectively deal with split words and homophones.Relying on the design ideas of machine learning,the clustering algorithm and vector machine mechanism are used to effectively avoid the defects of word order reversal and deep learning that cannot be timed.In addition,an incremental learning architecture based on the VFS architecture is designed.Compared with the ordinary streaming architecture,it also achieves more ideal learning efficiency on the basis of ensuring accuracy.On the basis of the content monitoring function,this article further implements the anti-tampering of website pages,mainly including monitoring and backup-based anti-tampering.First,the monitoring part uses the technical found ation provided by content monitoring to identify the changes that appear on the website and the potential dangers.Then,once it can be tampered with,it calls the anti-tampering mechanism to restore and lock the content of the website.Realized a relatively complete anti-tampering function of the website content.The optimized design can efficiently solve the basic needs of high concurrency and large capacity in the new era of security monitoring activities,and can effectively deal with various defects in traditional solutions.For machine learning,both accuracy and speed can be continuously increased.Therefore,there is a strong research significance for safety monitoring.The experimental part shows the successful achievement of the intended purpose by functional test and performance test of each module of the system.