Research On Safe Operation Technology Of Academic Website

With the development of Internet and computer technology,academic websites play a more and more important role in modern scientific research and provide many conveniences for researchers.While academic websites provide services to researchers,it is necessary to protect the academic resources in the website from being obtained illegally,so as to ensure the safe operation of the website system.Access control and anti-crawling technology are important to ensure that academic websites provide services to researchers normally and securely,and to protect the contents of academic websites.Therefore,it is of great practical significance to use these two technologies to design system to protect academic websites.The main function of access control system is to protect the academic resources and academic data in the academic website from being obtained illegally.The system is built on the basis of Role-Based Access Control model,and user group is added to the model to solve the problem of batch authorization.In addition,the system can determine whether subject is allowed to access the target resource according to the role granted to subject or the user group to which the access subject belongs,and provide role assignment rules.Anti-crawler system is mainly to prevent the harm of crawlers to academic websites,to prevent contents of websites from being stolen by crawlers,and to ensure the safe operation of websites.The system is based on an anti-crawler method combining heuristic rules with machine learning.This method combines heuristic rules for real-time crawler recognition and machine learning for high precision crawler recognition.Heuristic rules recognize crawler in real time according to the relevant features of the request of subject.Machine learning uses access logs of website to train classifier,which recognizes hidden crawlers that can not be recognized by heuristic rules.The part of experiment uses real dataset to evaluate the designed system.The experimental results prove the effectiveness of the designed access control system and the accuracy of the anti-crawler system.Moreover,the precision of the Random Forest classifier used by anti-crawler system is 90.5%.