HYBRID FANN-HE MODEL AND QoS PARAMETERS FOR SECURE AND SCALABLE ACCESS CONTROL IN ENVIRONMENTS OF CLOUD COMPUTING

Abstract

Cloud computing has become an essential technology for modern businesses, providing scalability and flexibility in data storage and processing. However, the increasing use of cloud computing has raised concerns about the security of sensitive information. A hybrid Fuzzy-ANN (FANN-HE) model with hybrid encryption and Quality of Service (QoS) parameters is proposed for managing access control in CC environments. The proposed model integrates Fuzzy logic and Artificial Neural Networks (ANNs) to achieve better performance in terms of scalability and security. The QoS parameters considered include response time, throughput, latency, and failure rate. Hybrid encryption (HE) is used to further security improvement of the access control system. The dynamic resource allocation techniques can be used to allocate resources based on the current workload to improve scalability. The model is evaluated using different datasets, and the performance shows that it outperforms traditional methods in terms of scalability, security, and efficiency. The proposed hybrid Fuzzy-ANN model with hybrid encryption and QoS parameters can be used as an effective tool for managing access control (AC) in cloud computing (CC) environments.