Cloud computing is a model for on-demand delivery of IT resources (e.g., servers, storage, databases, etc.) over the Internet with pay-as-you-go pricing. Although it provides numerous benefits to cloud service users (CSUs) such as flexibility, elasticity, scalability, and economies of scale, there is a large trust deficit between CSUs and cloud service providers (CSPs) that prevents the widespread adoption of this computing paradigm. While some businesses have slowly started adopting cloud computing with careful considerations, others are still reluctant to migrate toward it due to several data security and privacy issues. Therefore, the creation of a trust model that can evolve to reflect the true assessment of CSPs in terms of either a positive or a negative reputation as well as quantify trust level is of utmost importance to establish trust between CSUs and CSPs. In this paper, we propose a fuzzy-logic based approach that allows the CSUs to determine the most trustworthy CSPs. Specifically, we develop inference rules that will be applied in the fuzzy inference system (FIS) to provide a 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-logic based trust model is not limited to the CSUs as it can be used by the CSPs to promote their services through self-evaluation. To demonstrate the effectiveness of our proposed fuzzy-based trust model, we present case studies where several CSPs are evaluated and ranked based on the security index.

中文翻译：

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用于评估云服务提供商的安全就绪性的模糊推理系统（FIS）

云计算是一种模型，用于通过按需付费定价在Internet上按需交付IT资源（例如，服务器，存储，数据库等）。尽管它为云服务用户（CSU）提供了许多好处，例如灵活性，弹性，可伸缩性和规模经济，但是CSU与云服务提供商（CSP）之间存在巨大的信任赤字，这阻止了该计算范式的广泛采用。尽管有些企业已经开始谨慎考虑采用云计算，但是由于一些数据安全性和隐私问题，其他企业仍然不愿意向其迁移。因此，建立信任模型以建立CSU和CSP之间的信任至关重要，该信任模型可以发展以反映对CSP的正面或负面声誉的真实评估以及量化信任级别。在本文中，我们提出了一种基于模糊逻辑的方法，该方法允许CSU确定最值得信赖的CSP。具体来说，我们开发了将在模糊推理系统（FIS）中应用的推理规则，以为CSU提供定量的安全性指标。FIS的主要优点之一是它考虑了与衡量信任度相关的不确定性和歧义。此外，我们提出的基于模糊逻辑的信任模型不限于CSU，因为CSP可以使用它通过自我评估来促进其服务。