User behaviors attributes of database anomaly detection model
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 12
Abstract
This paper includes the description of designing a data-base anomalydetection system, whichis capable of being more precisein depictingthe behaviors of individuals and improving data-base abnormaldetecting correctness. In designing the system, the Aprioriapproach is used first and depends on the k-meansclusteringand the Apriorimethods.It is capable of more efficiently exploitingusers’behaviors, and the data-base abnormalmore efficient detecting. The relevantstudiesshow that Apriorimethodaccording to time efficiency and precision of detectionis more optimal than thesoleutilizationaccording to association rulesmining approachesApriorimethod.
Authors and Affiliations
SaifAldeen Salim Ahmed
Keywords
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- EP ID EP392984
- DOI 10.9790/9622-0712022935.
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