• Mojtaba Mohammadi
• Keshav Kishore

Cloud computing is a relatively new technology which is growing rapidly due to its distinctive features. It provides a way to access data from any place at any time. This feature makes cloud computing widely popular, because it reduces the burden of the users. Cloud computing provides various services like infrastructure, platform and software as a service. Due to these features, the efficiency of cloud has been greatly affected as a result of the increasing size of data on cloud. To overcome such a problem, the task security on data appears to be a promising option. Workflow security is a challenging task in cloud computing, considering user requirements and satisfaction. Another issue is the resource utilization due to the nature of cloud computing. In order to maintain and utilize resources in the cloud computing, a security mechanism is required. Many algorithms and protocols are used to manage the parallel processing used to enhance the performance of the CPU in the cloud environment. RBAC and RBAC-ABAC(HYBRID) models use variety of different approaches to improve the security of cloud. Our proposed model however, is based on the optimization of the total execution time as well as the total execution cost. Using intelligence optimization initialized by Pareto distribution, the results are found to be effective in compare to the existing methods. A hybrid model is used to converge the decision of Virtual Machine (VM) migration by its convergence to minimize cost and time as illustrated by the total execution time and total execution cost. It is concluded that our proposed hybrid model performs better in compare to the existing ABAC algorithms.

Role Based Access Control (ABAC), Attribute Based Access Control (ABAC), Context Aware Access Control, HA-RBAC, Role Explosion, Particle Swarm Optimization (PSO), Gray Wolf Optimizer (GWO), Pareto Distribution

"Enhancing Hybrid ACL Based Model by Optimizing Task Scheduling in Cloud", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.445-457, December-2018, Available :http://www.jetir.org/papers/JETIR1812757.pdf

"Enhancing Hybrid ACL Based Model by Optimizing Task Scheduling in Cloud", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp445-457, December-2018, Available at : http://www.jetir.org/papers/JETIR1812757.pdf