IEEE Access (Jan 2022)

The Assessment of Cloud Service Trustworthiness State Based on D-S Theory and Markov Chain

  • Ming Yang,
  • Tilei Gao,
  • Wanyu Xie,
  • Li Jia,
  • Tao Zhang

DOI
https://doi.org/10.1109/ACCESS.2022.3185684
Journal volume & issue
Vol. 10
pp. 68618 – 68632

Abstract

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The massive cloud service market is full of various services with uneven quality. Even the services that have passed the platform detection will have unknown trustworthiness problems in the actual use process. The risk environment of the cloud service determines that its trustworthiness is random. The static trustworthiness assessment results can only reflect the cloud service trustworthiness at a certain time, not enough to reflect the real trustworthiness of the cloud service. To objectively reflect the trustworthiness of the cloud service, it is necessary to further assess the cloud service trustworthiness state and its changes on the basis of trustworthiness level measurement. To solve this problem, this paper combs the trustworthiness indicators of the cloud service, puts forward an effective assessment method of cloud service trustworthiness level based on D-S theory, and puts forward the representation method of cloud service trustworthiness state and its transition state combined with Markov chain, so as to realize the effective assessment of cloud service trustworthiness state and its changes. Finally, through case analysis, it shows that the method proposed in this paper is feasible, can effectively assess the cloud service trustworthiness state and its changes, and provide users with detailed assessment results, so as to help users make reasonable service selection and trustworthiness management. This research has important significance for ensuring the cloud service trustworthiness and improving the cloud service market security.

Keywords