Intelligent Role-Based Access Control Model and Framework Using Semantic Business Roles in Multi-Domain Environments

Rubina Ghazal,Hani Alquhayz,Basit Raza,Ahmad Raza Shahid,Ahmad Kamran Malik,Nauman Qadeer

doi:10.1109/access.2020.2965333

Abstract

Today's rapidly developing communication technologies and dynamic collaborative business models made the security of data and resources more crucial than ever especially in multi-domain environments like Cloud and Cyber-Physical Systems (CPS). It enforced the research community to develop enhanced access control techniques and models for resources across multi-domain distributed environments so that the security requirements of all participating organizations can be fulfilled through considering dynamicity of changing environments and versatility of access control policies. The popularity of Role-Based Access Control (RBAC) model is irrefutable because of low administrative overhead and large-scale implementation in business organizations. However, it does not incorporate the dynamically changing policies and lacks semantically meaningful business roles which could have a diverse impact upon access decisions in multi-domain business environments. This paper describes our proposed novel access control framework that uses semantic business roles and intelligent agents through implementation of our Intelligent RBAC (I-RBAC) model. It encompasses occupational entitlements as roles for multiple domains. We use the dataset of original occupational roles provided by Standard Occupational Classification (SOC), USA. The novelty of the paper lies in developing a core I-RBAC ontology using real-world semantic business roles and intelligent agent technologies together for achieving required level of access control in highly dynamic multi-domain environment. The intelligent agents use WordNet and bidirectional LSTM deep neural network for automated population of organizational ontology from unstructured text policies. This dynamically learned organizational ontology is further matched with our core I-RBAC ontology in order to extract unified semantic business roles. The proposed I-RBAC model is mathematically described and the overall I-RBAC framework and its implementation architecture is explained. At the end, the I-RBAC model is validated through the implementation results that show a linear runtime trend of the model in presence of a large number of permission assignments and multiple queries.

Highlights

Information is one of the most significant assets of an organization and requires an appropriate protection
The I-Role-Based Access Control (RBAC) framework describes the procedures of knowledge management and access decision
WORK In this paper, we have focused on the need for a security mechanism that can support today’s dynamically changing environments and presented our proposed Intelligent Role Based Access Control (I-RBAC) model and framework which fulfills these requirements

Summary

Introduction

Information is one of the most significant assets of an organization and requires an appropriate protection. Organizations use authentication and authorization to ensure the. The associate editor coordinating the review of this manuscript and approving it for publication was Xiwang Dong. A user always needs authentication before her authorization to perform an activity. An effective information security mechanism decides that who should have access to which information or resource. Another fundamental question in information security is that how to control the access to resources to protect them from unauthorized modification [1].

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