Enhancement of Security in Cloud Computing Using Optimal Risk Access Control Model

This paper develops an Optimal Risk Access Control Model (ORACM) for enhancing security in cloud computing. In this proposed model, three important risk aspects are considered such as environment attribute, resource attribute and subject attribute. Based on these factors, the suggested risk validation indexes were created, and by fusing Adaptive Snake Optimization (ASO) and Policy Approach Access Control (PAAC), the risk validation computation method would be quantitatively validated. In the PAAC, the optimization method is taken into account while choosing the decision. Based on the validation, optimization and choosing the best risk decision is reducing waiting time. conventional access control continues to receive access needs as extended as they are genuine once the architecture is in an emergency state (like when the CPU and memory remain saturated), raising the danger of a system crash. Consider a case where the system is presently in an emergency, on the other hand. The authentication token may be misused, leading to the unauthorized access of system resources and services, if the security of the primary environment depreciates. The suggested strategy is put into practice, and its effectiveness is assessed by taking into account performance indicators including waiting time, convergence analysis, and CPU usage. It is also contrasted with traditional approaches.