—Data mining is widely used to identify interesting,potentially useful and understandable patterns from a largedata repository. With many organizations focusing on webbasedon-line transactions, the threat of security violationshas also increased. Since a database stores valuableinformation of an application, its security has started gettingattention. An intrusion detection system (IDS) is used todetect potential violations in database security. In everydatabase, some of the attributes are considered moresensitive to malicious modifications compared to others. Wepropose an algorithm for finding dependencies amongimportant data items in a relational database managementsystem. Any transaction that does not follow thesedependency rules are identified as malicious. We show thatthis algorithm can detect modification of sensitive attributesquite accurately. We also suggest an extension to the Entity-Relationship (E-R) model to syntactically capture thesensitivity levels of the attributes.
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