Minimize the False Positive Rate in a Database Intrusion Detection System

A database intrusion detection system (DIDS) is used to detect potential violations in database security. DIDS follows other traditional database security mechanisms and network security mechanisms such as firewall and network intrusion detection. Therefore, it faces the intrusion from internal users or the intrusion that can be passed through other security layers. This means that the number of intrusion event is rare compared to the number of the normal event. Therefore, it is not efficient to raise a large number of false alarms to achieve a high detection rate. This paper introduces an enhancement for the data dependency model and integrates it with access control to override the high rate of false alarm and increase the detection rate.