Credibility measurement of cloud services based on information entropy and Markov chain

Despite the rapid advancement of cloud computing technologies, user skepticism about service credibility remains a major barrier to adoption of cloud services. At present, there is not a comprehensive and systematic understanding of the factors that affect the credibility of cloud services. In view of the uncertainty and correlation between the factors of cloud service credibility, this study analyzed the user's demand for credit and credibility. The cloud service credibility attributes were divided into six dimensions: cloud service visibility, controllability, security, reliability, cloud service provider viability and user satisfaction. A cloud service credibility measurement model combining information entropy and Markov chain was established, which could calculate the uncertainty of each factor in the attribute model. The degree of influence on the credibility of cloud service and the credibility level of cloud service provider are calculated in the model. The experimental validation demonstrates that the information entropy and Markov chain model achieves a 15% improvement in prediction accuracy compared to traditional AHP methods, with particularly notable enhancements in dynamic scenario adaptability, which helps users make informed decisions when selecting cloud services.