Research on Data Risk Control Strategies for Hybrid Cloud

Abstract

Objective: Hybrid cloud provides an efficient and relatively secure service, widely used in commercial and public affairs. There are already several specific risk control strategies for hybrid clouds in the existing cloud computing literature, but there is still a need to design data risk control strategies that cater to users with different risk preferences. Methods: Firstly, by using a classification method, we propose four data risk control strategies that are suitable for different cloud environments. Then, we use the queueing theory to model the hybrid cloud system and derive some relevant indicators of system performance. Results: We propose four new risk control strategies for the personalized needs of enterprises in different scenarios, namely, L-control strategy, LOS1-control strategy, LOS2-control strategy, and (L,q)-control strategy. Conclusions: It is more practical to use a hybrid cloud system for the protection of data security. This work proposes four risk control strategies for different situations to help companies with risk control, namely, L-control strategy, LOS1-control strategy, LOS2-control strategy, and (L,q)-control strategy. These risk control strategies provide theoretical assistance for exploring the allocation of cloud resources.