Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3507
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dc.contributor.authorLu, G-
dc.contributor.authorYi, J-
dc.contributor.authorLü, K-
dc.coverage.spatial5en
dc.date.accessioned2009-07-21T13:13:36Z-
dc.date.available2009-07-21T13:13:36Z-
dc.date.issued2007-
dc.identifier.citationProceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery, 24-27 Aug 2007en
dc.identifier.isbn0-7695-2874-0-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/3507-
dc.description.abstractA new type of database anomaly is described by addressing the concept of Cumulated Anomaly in this paper. Dubiety-Determining Model (DDM), which is a detection model basing on statistical and fuzzy set theories for Cumulated Anomaly, is proposed. DDM can measure the dubiety degree of each database transaction quantitatively. Software system architecture to support the DDM for monitoring database transactions is designed. We also implemented the system and tested it. Our experimental results show that the DDM method is feasible and effective.en
dc.format.extent410009 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherIEEEen
dc.titleStatistical and fuzzy approach for database securityen
dc.typeConference Paperen
Appears in Collections:Business and Management
Brunel Business School Research Papers

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