Algorithm for detecting illegal links using the association rule for improving the web attack detection accuracy of web application firewall

Nguyen Manh Thang

Abstract


Illegal links appear more often through social networks with "dizzying" speed. When users click on a "malicious" link it can bring them potential danger. One of the most popular social networks is Facebook. It is one of the ways for hackers to share malicious links. For example, there are many advertisements with links, and when the user clicks on these links all the information of the user practically falls into the hands of hackers. Hence, a system administrator needs to check requests before running them on the server to ensure security. One of the most common approaches is the Web Application Firewall (WAF). The article presents an algorithm for detecting illegal links based on tf-idf technology for evaluating the "importance" of keywords, symbols in the links of user requests from the user's browser with machine learning method to improve the accuracy of identifying illegal links.


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