University of North Alabama
Managing hierarchical and ne grained DBMS policies for a large number of users is a challenging task and it increases the probability of introducing mis-configurations and anomalies. In this paper, the authors present a formal approach to discover anomalies in database policies using Binary Decision Diagrams (BDDs) which allow finer grain analysis and scalability. They present and formalize intra-table and inter-table redundancy anomalies using the popular MySQL database server as a case study. They also provide a mechanism for improving the performance of policy evaluation by upgrading rules from one grant table to another grant table. They implemented their proposed approach as a tool called MySQLChecker.