Malicious Modification Attacks by Insiders in Relational Databases: Prediction and Prevention

This paper investigates the problem of malicious modifications by insiders in relational databases. It presents an algorithm that shows how to construct insiders´ Modification Graphs, which demonstrate the authorized and unauthorized data items in which insiders can make changes. Two methods are provided to prevent modification attacks. The first method prevents attacks by hiding dependencies between data items. The second method prevents attacks by denying write access to some data items. We present the cut algorithm that determines which dependencies should be hidden to prevent modification attacks on sensitive data items. In addition, we use modification graphs to determine which write accesses should be denied in order to prevent such attacks.