Toward Implementing Spatio-Temporal RBAC Extensions

Abstract

Role-Based Access Control (RBAC) restricts unauthorized user accesses by ensuring that only the permissions necessary for executing the respective tasks by the users are available through the roles assigned to them. In order to effectively deploy and sustain RBAC in an organization, a set of roles needs to be designed. This can be done using an approach known as role mining. In many cases, it may be essential to limit the accessibility of the roles to certain locations and time periods. Such kind of location and time dependent availability of roles can be enforced by the spatio-temporal extensions of the RBAC model. The implementation of these extended models requires the creation of spatially and temporally constrained roles which cannot be directly done using the traditional role mining algorithms. In this paper, we propose an approach known as spatio-temporal role mining to generate the roles for setting up spatio-temporal RBAC. We describe a suitable representation for depicting the input to spatio-temporal role mining, formally define the Spatio-Temporal Role Mining Problem (STRMP) and propose an algorithm for solving it. Experimental results obtained from synthetic and real-world datasets provide the performance evaluation of our proposed approach.