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INFOSCALE
2007
ACM

A dubiety-determining based model for database cumulated anomaly intrusion

9 years 5 months ago
A dubiety-determining based model for database cumulated anomaly intrusion
— The concept of Cumulated Anomaly (CA), which describes a new type of database anomalies, is addressed. A typical CA intrusion is that when a user who is authorized to modify data records under certain constraints deliberately hides his/her intentions to change data beyond constraints in different operations and different transactions. It happens when some appearing to be authorized and normal transactions lead to certain accumulated results out of given thresholds. The existing intrusion techniques are unable to deal with CAs. This paper proposes a detection model, Dubiety-Determining Model (DDM), for Cumulated Anomaly. This model is mainly based on statistical theories and fuzzy set theories. It measures the dubiety degree, which is presented by a real number between 0 and 1, for each database transaction, to show the likelihood of a transaction to be intrusive. The algorithms used in the DDM are introduced. A DDM-based software architecture has been designed and implemented for m...
Gang Lu, Junkai Yi, Kevin Lü
Added 26 Oct 2010
Updated 26 Oct 2010
Type Conference
Year 2007
Where INFOSCALE
Authors Gang Lu, Junkai Yi, Kevin Lü
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