Automated Semantic Role Mining Using Intelligent Role Based Access Control in Globally Distributed Banking Environment

Globally distributed banking environment need proper access control to ensure secure information sharing and collaboration among employees. Although Role Based Access Control (RBAC) is widely used, it falls short in adapting to the dynamic nature of global IT systems and complex real-world business roles. This work is an implementation of our already proposed Intelligent Role Based Access Control (I-RBAC) model that utilizes intelligent software agents to automate semantic role mining process in globally distributed collaborative banking environment where employees are expected to play multiple roles at multiple times based upon their profile and assigned tasks under limitations of provided banking policies. The information about roles, permissions, policies, and constraints is encapsulated in ontologies and Intelligent agents automatically extract semantic knowledge from employee’s profiles and banking policies that are shared as text files. Subsequently, automated semantic role mining is achieved through agent-driven reasoning. Experimental results have demonstrated promising accuracy in the mined roles.