A Fuzzy-Logic Approach for Evaluating a Cloud Service Provider

John Mitchell, S. Rizvi, J. Ryoo
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引用次数: 13

Abstract

Cloud computing represents the next evolutionary step in the realm of IT and offers a multitude of advantages over traditional computing models. However, there is a large trust deficit between cloud service users (CSUs) and cloud service providers (CSPs) that prevents the widespread adoption of the cloud among business professionals. Businesses are reluctant to migrate to the cloud due to the numerous security issues which affect data confidentiality and integrity. Therefore, a trust model is required to establish the positive reputation of the CSP. In this paper, we propose a fuzzy-logic based approach that allows the CSUs to determine the most trustworthy CSPs. Specifically, we develop the inference rules that will be applied in the fuzzy inference system (FIS) to provide the quantitative security index to the CSUs. One of the main advantages of the FIS is that it considers the uncertainties and ambiguities associated with measuring trust. Moreover, our proposed fuzzy based trust model is not limited to the CSU since it can be used by the CSPs in a self-evaluation process to promote improvement. To demonstrate the effectiveness of our proposed fuzzy based trust model, we present a case study where several popular CSPs are evaluated and ranked based on the security index.
评估云服务提供商的模糊逻辑方法
云计算代表了IT领域的下一个进化步骤,并提供了比传统计算模型更多的优势。然而,云服务用户(csu)和云服务提供商(csp)之间存在巨大的信任赤字,这阻碍了云在业务专业人员中的广泛采用。由于影响数据机密性和完整性的众多安全问题,企业不愿意迁移到云。因此,需要一个信任模型来建立CSP的正面声誉。在本文中,我们提出了一种基于模糊逻辑的方法,允许csu确定最值得信赖的csp。具体来说,我们开发了将应用于模糊推理系统(FIS)的推理规则,为csu提供定量的安全指标。FIS的主要优点之一是它考虑了与度量信任相关的不确定性和模糊性。此外,我们提出的基于模糊的信任模型并不局限于CSU,因为csp可以在自我评估过程中使用它来促进改进。为了证明我们提出的基于模糊信任模型的有效性,我们提出了一个案例研究,其中几个流行的csp基于安全指数进行评估和排名。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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