An Administrative Model for Role-Based Access Control Using Hierarchical Namespace

Access Control is an important mechanism of information security. Role-Based Access Control is a famous access control approach with good flexibility. RBAC96 and ARBAC97 are classical RBAC models. The ARBAC97 model facilitates decentralized administration of RBAC. However, ARBAC97 has some shortcomings in the case of being used in an organization with autonomous subsidiaries. The member of an administrative role can operate directly in the role range of a junior administrative role, which violates the autonomy of subsidiaries. We propose a new model named N-RBAC to overcome this weakness. In NRBAC, roles are arranged according to a hierarchical namespace structure. Thus the role hierarchy is constructed in a local space instead of in a global space. The N-RBAC model does a better work in decentralized role administration in those organizations composed of autonomous subsidiaries

Analyzing temporal role based access control models

Today, Role Based Access Control (RBAC) is the de facto model used for advanced access control, and is widely deployed in diverse enterprises of all sizes. Several extensions to the authorization as well as the administrative models for RBAC have been adopted in recent years. In this paper, we consider the temporal extension of RBAC (TRBAC), and develop safety analysis techniques for it. Safety analysis is essential for understanding the implications of security policies both at the stage of specification and modification. Towards this end, in this paper, we first define an administrative model for TRBAC. Our strategy for performing safety analysis is to appropriately decompose the TRBAC analysis problem into multiple subproblems similar to RBAC. Along with making the analysis simpler, this enables us to leverage and adapt existing analysis techniques developed for traditional RBAC. We have adapted and experimented with employing two state of the art analysis approaches developed for RBAC as well as tools developed for software testing. Our results show that our approach is both feasible and flexible

Role of Access Control in Information Security: A Security Analysis Approach

Information plays a vital role in decision-making and driving the world further in the ever-growing digital world. Authorization, which comes immediately after authentication, is essential in restricting access to information in the digital world. Various access control models have been proposed to ensure authorization by specifying access control policies. Security analysis of access control policies is a highly challenging task. Additionally, the security analysis of decentralized access control policies is complex because decentralization simplifies policy administration but raises security concerns. Therefore, an efficient security analysis approach is required to ensure the correctness of access control policies. This chapter presents a propositional rule-based machine learning approach for analyzing the Role-Based Access Control (RBAC) policies. Specifically, the proposed method maps RBAC policies into propositional rules to analyze security policies. Extensive experiments on various datasets containing RBAC policies demonstrate that the machine learning-based approach can offer valuable insight into analyzing RBAC policies