Trusted reasoning-role-based access control for cloud computing environment

• Main Author: Abdul Rauf, Abdul Rauf
• Format: Thesis
• Language: English
• Published: 2019
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/98249/1/AbdulRaufPSC2019.pdf; http://eprints.utm.my/id/eprint/98249/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:141927

Cloud computing has become the new standard in the fast-growing industry of information technology. This poses new challenges to the existing access control models, as the new computing paradigm is highly-distributed and multi-tenancy. The existing access control models are not strong enough due to unavailability of strong multiple relationships between user and resources. In addition, monitoring activities of users to protect the cloud resources is weak. In these contexts, malicious user must be identified for the protection of sensitive data and to limit the access of the user to the resources. This research developed an enhanced access control model for cloud computing, namely Trusted Reasoning-Role-Based Access Control for Cloud Computing Environment (TR2BAC) model. The model consists of four components. The first component is a dimensional domain for strong multiple relations between resources and user management, whereas the second component is reason-based access mechanism to limit users access based on defined reasoning principle. The third component is the trust module that identifies trusted/malicious users, and the fourth component ensures secure data access that classifies and labels the data according to the level of its sensitivity. The resources are then secured accordingly. Simulation results revealed that the performance of the proposed model improved in comparison to the existing state of the art techniques in terms of throughput by 25% and Permission Grants results by 35%. In terms of user authorization, the access time improved by 95% of the total access time which is about 7.5 seconds. In conclusion, this research has developed an enhanced access control model for cloud computing environment that can be used to protect the privacy of users as well as cloud resources from inside and outside attacks.