Role Mining with Probabilistic Models
Source: UC AB
Role mining pursues the goal of finding a Role-Based Access Control (RBAC) configuration that is extracted from the assignment of users to access permissions given by an access-control matrix. Most approaches to role mining work by constructing a large set of candidate roles and use a greedy selection strategy to iteratively pick a small sub-set such that the differences between the resulting RBAC configuration and the access control matrix are minimized. In this paper, the authors advocate an alternative approach that recasts role mining as an inference problem rather than a lossy compression problem.