A network access control mechanism based on role and behavior

Current Role-Based Access Control (RBAC) can´t assign permissions dynamically and can´t update access control policies automatically. In this paper we present a new network access control (NAC) mechanism based on role and behavior (RB-NAC) which enhances role-based access control by establishing clusters of behavior to limit permissions of user dynamically and incorporating an incremental-learning algorithm to update the policies without manual intervention. RB-NAC as an enhanced access control mechanism shows its efficient flexibility and scalability in access control.