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<p>As cloud computing advances, user expectations for cloud service quality have increased significantly. Each cloud service model presents distinct service features. By adhering to principles of scientific rigor, comprehensiveness, and measurability, security risk measurement indicators were selected and a cloud service security risk assessment framework was established. This framework encompasses three primary security attributes: privacy risk, technical risk, and business and operational management risk, along with 21 measurement indicators. Given the uncertainty, diversity, and potential losses in various cloud service application scenarios, an effective risk measurement approach was proposed. This method integrates risk attribute modeling with an Information Entropy and Markov Chain (IE-MC) algorithm. Test results demonstrate that the cloud service security risk model utilizing the IE-MC algorithm is both effective and applicable across different measurement methods, offering enhanced precision in practical cloud service security assessments.</p>

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A cloud service security risk measurement method based on information entropy and Markov chain

  • 期刊论文

  • 发表日期：

    2025年8月19日

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  • Jian Yu,
  • Xiangmei Xiao

摘要

As cloud computing advances, user expectations for cloud service quality have increased significantly. Each cloud service model presents distinct service features. By adhering to principles of scientific rigor, comprehensiveness, and measurability, security risk measurement indicators were selected and a cloud service security risk assessment framework was established. This framework encompasses three primary security attributes: privacy risk, technical risk, and business and operational management risk, along with 21 measurement indicators. Given the uncertainty, diversity, and potential losses in various cloud service application scenarios, an effective risk measurement approach was proposed. This method integrates risk attribute modeling with an Information Entropy and Markov Chain (IE-MC) algorithm. Test results demonstrate that the cloud service security risk model utilizing the IE-MC algorithm is both effective and applicable across different measurement methods, offering enhanced precision in practical cloud service security assessments.