Entropy-based classification of trust factors for cloud computing

Ankita Sharma, Puja Munjal, H. Banati
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引用次数: 3

Abstract

Cloud computing has now been introduced in organisations all around the globe. With the developing prevalence of grid and distributed computing, it has become incredibly important to maintain security and trust. Researchers have now begun concentrating on mining information in cloud computing and have begun distinguishing the basic factor of moral trust. Moral angles in the cloud rely upon the application and the present conditions. Data mining is a procedure for distinguishing the most significant data from a lot of irregular information. In this paper, a three phased methodology is adopted, involving machine learning techniques to discover the most important parameter on which trust is based in the cloud environment. The methodology was then implemented on data sets, proving privacy is the most important factor to calculate ethical trust in cloud computing. The results can be employed in real cloud environments to establish trust as service providers can now consider privacy as the main issue in this relatively new distributed computing environment.
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基于熵的云计算信任因子分类
云计算现在已经被引入到全球各地的组织中。随着网格和分布式计算的发展,维护安全和信任变得非常重要。研究人员现在已经开始专注于在云计算中挖掘信息,并开始区分道德信任的基本因素。云中的道德角度取决于应用和现状。数据挖掘是一种从大量不规则信息中识别最重要数据的过程。在本文中,采用了一个三阶段的方法,涉及机器学习技术来发现云环境中信任所基于的最重要参数。然后将该方法应用于数据集,证明隐私是云计算中计算道德信任的最重要因素。研究结果可用于真实的云环境,以建立信任,因为服务提供商现在可以将隐私视为这个相对较新的分布式计算环境中的主要问题。
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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