Knowledge Based Access Control a model for security and privacy in the Big Data

Lamia El Haourani, A. A. E. Kalam, A. A. Ouahman
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引用次数: 5

Abstract

The most popular features of Big Data revolve around the so-called "3V" criterion: Volume, Variety and Velocity. Big Data is based on the massive collection and in-depth analysis of personal data, with a view to profiling, or even marketing and commercialization, thus violating citizens' privacy and the security of their data. In this article we discuss security and privacy solutions in the context of Big Data. We then focus on access control and present our new model called Knowledge-based Access Control (KBAC); this strengthens the access control already deployed in the target company (e.g., based on "RBAC" role or "ABAC" attributes for example) by adding a semantic access control layer. KBAC offers thinner access control, tailored to Big Data, with effective protection against intrusion attempts and unauthorized data inferences.
基于知识的访问控制:大数据中的安全与隐私模型
大数据最受欢迎的特征围绕着所谓的“3V”标准:体积(Volume)、种类(Variety)和速度(Velocity)。大数据是基于对个人数据的大量收集和深入分析,以分析、甚至营销和商业化为目的,从而侵犯了公民的隐私和数据安全。在本文中,我们将讨论大数据背景下的安全和隐私解决方案。然后,我们将重点放在访问控制上,并提出了基于知识的访问控制(KBAC)模型;这通过添加语义访问控制层来加强目标公司中已经部署的访问控制(例如,基于“RBAC”角色或“ABAC”属性)。KBAC提供更薄的访问控制,为大数据量身定制,有效防止入侵企图和未经授权的数据推断。
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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