An assessment model for cloud service security risk based on entropy and support vector machine

Cloud services are open, shared, and complex. These characteristics will lead to many security risks and will affect the development of cloud services. Therefore, it is necessary to identify and measure the security risks of cloud services. However, there are still many deficiencies in this area. In light of this, this paper carries out an in-depth study from the perspective of technical security risk. Firstly, this paper combines the three aspects on cloud service security problems, objectives, and technologies. It attempts to explore the technological solutions to get security risk problems to achieve the expected security goals, and establish the cloud service technology security risk index system. Secondly, because of the strong subjectivity and the deficiency of the data obtained from cloud service providers, this paper establishes a cloud service security risk assessment model based on entropy weight theory and multi-classification support vector machine. Finally, the experimental results show that the evaluation model is feasible and effective.