Anomaly SQL SELECT-statement detection using entropy analysis

Simple item page
dc.contributor.authorThreepak, Thanunchai
dc.contributor.authorWatcharapupong, Akkradach
dc.date.accessioned2026-08-06T10:09:11Z
dc.date.available2026-08-06T10:09:11Z
dc.date.issued2014-01-01
dc.description.abstractDatabase 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.
dc.identifier.citationLecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 8397 LNAI(PART 1), 301-309, 2014
dc.identifier.doi10.1007/978-3-319-05476-6_31
dc.identifier.issn03029743
dc.identifier.other2-s2.0-84899979135
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/5584
dc.sourceLecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
dc.subjectAnomaly Detection
dc.subjectDatabase Security
dc.subjectEntropy Analysis
dc.subjectSQL Injection
dc.titleAnomaly SQL SELECT-statement detection using entropy analysis
dc.typeConference Paper

Files

Collections

Research