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Anomaly SQL SELECT-statement detection using entropy analysis
Date Issued
January 1, 2014
Type
Conference Paper
Abstract
Database systems are often intruded because they store valuable information and can be accessed through Internet web applications which sometimes are not developed with security in mind. Attackers can inject some crafted inputs to those programs that work on database systems so that some unexpected results occur. We analyze the database system log files, focus on query statements (SQL SELECT statements), using the Shannon entropy to detect such anomaly attempts that would change conditional entropy significantly. Our experiment shows that the proposed anomaly detection using entropy analysis is effective. © 2014 Springer International Publishing Switzerland.
Citation
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 8397 LNAI(PART 1), 301-309, 2014