With the increased development of cloud computing, access control is of paramount importance as a security concern. Numerous access control approaches exist in various published works. Among such prevalent approaches, Role Based Access Control (RBAC) model for enterprise cloud is scope of the present study. Nowadays, resource management, along with the primary aspect of security concern, is also addressed by the access control policies through restricting the allocation of the computing resources based on the roles assigned to the users. Keeping in view of the upcoming peak-load requirements or certain constraints, the policies may have ineffective resource allocation which leads to over/under-utilization of the resources over a period of time. So, an adaptive access control mechanism is desired that can vary their policies dynamically for resource allocation depending upon the ongoing requirements, for its efficient utilization. This is presented in the form of an adaptive access control mechanism (AACM) that aims to effectively utilize the computing resources in the enterprise cloud. It will aid in identifying the over- and under-allocation of the computing resources defined as access control policies and redefine these policies so as to ensure efficient and effective usage of the enterprise cloud resources. In this paper, this novel approach to access control mechanism for the enterprise cloud is represented using ontologies developed in Protégé. This is developed by identification of the underlying concepts and their interrelationships through properties, in the enterprise cloud. The presented ontology is for the sake of knowledge representation to represent knowledge and facts.
Generalized Algebraic Deadlock Avoidance Policies for Sequential Resource Allocation Systems
