A dubiety-determining based model for database cumulated anomaly intrusion
Gang Lu, Junkai Yi, Kevin Lü · 2007
In this paper, the concept of Cumulated Anomaly is addressed, which describes a new type of database anomalies. A detection model, Dubiety-Determining Model (DDM), is proposed for it. The DDM can measure the dubiety degree of each database transaction quantitatively. We conducted experiments basing on the DDM. In our experiments, the DDM method calculates a real number for each audit record. That number is called dubiety degree, which indicates the possibility of being anomaly for each transaction. The experimental results demonstrate basic features, the feasibility, and the effectiveness of the method.