CBRid4SQL: a CBR intrusion detector for SQL injection attacks
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
idMAS-SQL: Intrusion Detection Based on MAS to Detect and Block SQL injection through data mining
Information Sciences: an International Journal
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The ubiquity of web applications has led to an increased focus on the development of attacks targeting these applications. One particular type of attack that has recently become prominent is the SQL injection attack. SQL injection attacks can potentially result in unauthorized access to confidential information stored in a backend database. In this paper we describe an anomaly based approach which utilizes the character distribution of certain sections of HTTP requests to detect previously unseen SQL injection attacks. Our approach requires no user interaction, and no modification of, or access to, either the backend database or the source code of the web application itself. Our practical results suggest that the model proposed in this paper is superior to existing models at detecting SQL injection attacks. We also evaluate the effectiveness of our model at detecting different types of SQL injection attacks.