Design of Security and Privacy Models for Optimizing the Selection of Cloud Service Providers in Cloud Computing Environments

Abstract

In order to solve the problem of difficult access to personalized and high-quality services for cloud users, the author proposes a security and privacy model for optimizing the selection of cloud service providers in the cloud computing environment. This model first divides user nodes into three types based on historical transactions between nodes: familial nodes, unfamiliar nodes, and ordinary nodes; Secondly, in order to protect the privacy information feedback from nodes, a trust evaluation agent is introduced as the subject of trust evaluation, and a trust value evaluation method based on user type is designed; Finally, considering the dynamic nature of trust, a new trust update mechanism based on service quality is proposed by combining transaction time and transaction amount. The experimental results show that compared with the AARep model and PeerTrust model, this model not only has advantages in scenarios with a lower proportion of malicious nodes, but also improves interaction success rates by 12% and 18%, respectively, in harsh scenarios where the proportion of malicious nodes exceeds 72%. This model overcomes the low success rate of interaction between user nodes and service nodes in cloud environments and has strong resistance to malicious behavior.