Tranquilize Role Mining using HR (Heuristic Random) Approach

Abstract

Role Based Access Control (RBAC) plays a vital role in the administration of large enterprises. Based on the role the user permissions are assigned. Role mining has quiet complex in mapping role and tranquilizing. In this paper we address the complexity of role mining that arises in RBAC system. Here we propose an HR approach to tranquilize the role mining complexity in administration. First, we identify the user permission; second, the roles are assigned with weight; third, the user-permission assignments are clustered using clustering co-efficient. Finally, the user-permission assignments are pruned by using the HR (Heuristic Random) approach. HR approach is measured using multi objective function such as Threshold, Maximal bicliques and clustering co-efficient. We proved that pruned user-permission assignments using HR approach yield better threshold value when comparing with the deterministic and random approach.