StateMiner: An Efficient Similarity-Based Approach for Optimal Mining of Role Hierarchy

摘要

Recently, there is a growing trend of organizations migrating to RBAC because of the economic benefits that RBAC provides, and the ease of administration. In order to deploy an RBAC system, one requires to first identify a complete set of roles. This process, known as role engineering, has been identified as one of the costliest tasks in migrating to RBAC. Several approaches have been proposed that mostly use data mining techniques to discover roles. However, most of them do not consider the existing roles and try to define everything from scratch, which is not acceptable for organizations that already have an RBAC system in place. In this paper, we formally define the problem of mining role hierarchy with minimal perturbation and present StateMiner, a heuristic solution to find an RBAC state as similar as possible to both the existing state and the optimal state. We present experiments to demonstrate the effectiveness of our approach.