Suspicious user tracking based on web data analysis

Web application has become one of the main network applications. The security in web application systems is very important. In this paper we present a method for tracking suspicious users based on web data analysis. Based on a browser/server model, internet flow data are stored in the server and outliers considered as the suspicious users are detected with web data analysis. The behaviors of these suspicious users are tracked and those browsed web pages are recorded in database. By replaying the visited web pages, the proposed method is able to monitor the given suspicious users, which can benefit intranet network security.