A Probabilistic Approach to Hybrid Role Mining


Role mining algorithms address an important access control
problem: configuring a role-based access control system.
Given a direct assignment of users to permissions, role
mining discovers a set of roles together with an assignment
of users to roles. The results should closely agree with the
direct assignment. Moreover, the roles should be understandable
from the business perspective in that they reflect
functional roles within the enterprise. This requires hybrid
role mining methods that work with both direct assignments
and business information from the enterprise.

In this paper, we provide statistical measures to analyze
the relevance of different kinds of business information for
defining roles. We then present an approach that incorporates
relevant business information into a probabilistic
model with an associated algorithm for hybrid role mining.
Experiments on actual enterprise data show that our algorithm
yields roles that both explain the given user-permission
assignments and are meaningful from the business perspective.