Intrusion detection in web applications: Evolutionary approach

A novel approach based on applying a modern meta-heuristic Gene Expression Programming (GEP) to detecting Web application attacks is presented in the paper. This class of attacks relates to malicious activity of an intruder against applications, which use a database for storing data. The application uses SQL to retrieve data from the database and Web server mechanisms to put them in a Web browser. A poor implementation allows an attacker to modify SQL statements originally developed by a programmer, which leads to stealing or modifying data to which the attacker has not privileges. While the attack consists in modification of SQL queries sent to the database, they are the only one source of information used for detecting attacks. Intrusion detection problem is transformed into classification problem, which the objective is to classify SQL queries between either normal or malicious queries. GEP is used to find a function used for classification of SQL queries. Experimental results are presented on the basis of SQL queries of different length. The findings show that the efficiency of detecting SQL statements representing attacks depends on the length of SQL statements. Additionally we studied the impact of classification threshold on the obtained results.