Information Security Assessment in Big Data Environment using Fuzzy Logic

Kanika Sharma, A. Shankar, Prabhishek Singh
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引用次数: 7

Abstract

In recent years, it has been observed that disclosure of information leads to the risk. Without restrict the accessibility of information providing security is difficult. So, there is a demand of time to fill the gap between security and accessibility of information. In fact, security tools should be usable for improving the security as well as the accessibility of information. Though security and accessibility are not related directly, but some of their factors indirectly affect each other. Attributes play an important role in connecting the gap among security and accessibility. In this paper, finds the main attributes of security and accessibility that impact directly and indirectly each other such as confidentiality, integrity and availability and severity. The significance of every attribute in terms of their weight is important for their effect on the overall security during the big data security life cycle process. To calculate proposed work, researchers used the Fuzzy Analytic Hierarchy Process (Fuzzy AHP).
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基于模糊逻辑的大数据环境下信息安全评估
近年来,人们观察到信息披露导致风险。没有限制信息的可访问性,提供安全是困难的。因此,填补信息的安全性和可访问性之间的差距需要时间。事实上,安全工具应该可用于提高信息的安全性和可访问性。安全性与可访问性虽然没有直接的关系,但其中的一些因素是相互间接影响的。属性在连接安全性和可访问性之间的差距方面发挥着重要作用。本文发现了安全性和可访问性之间直接或间接影响的主要属性,如保密性、完整性、可用性和严重性。在大数据安全生命周期过程中,每个属性的权重对整体安全的影响非常重要。为了计算建议的工作量,研究人员使用了模糊层次分析法(Fuzzy AHP)。
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