Context aware Secure Collaborative Business Intelligence

Veena N. Jokhakar
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Abstract

To enable efficient decision making, professionals need to collaborate with individuals with data being a collected from various sources like distributed clouds for storage, very large databases and social media with authentication and validation is needed for access to relevant roles. Further application of machine learning to deal with unlawful actions. This paper proposes a Context Aware Secure Collaborative Business Intelligence Framework (CASCBF) to address the same. CASCBF is divided into three layers. Multiple sources of data provide different levels of abstraction and granularity of access control to different roles. To control different types of assemblage of data resources from distributed sources and provide right access to users to the edge of the network is a core challenge.
上下文感知的安全协作商业智能
为了实现有效的决策制定,专业人员需要与个人协作,处理从各种来源收集的数据,如用于存储的分布式云、非常大的数据库和需要身份验证和验证以访问相关角色的社交媒体。进一步应用机器学习来处理非法行为。本文提出了一种上下文感知安全协同商业智能框架(CASCBF)来解决这一问题。CASCBF分为三层。多个数据源为不同的角色提供不同级别的抽象和粒度的访问控制。如何控制来自分布式数据源的不同类型的数据资源组合,并为用户提供对网络边缘的正确访问是一个核心挑战。
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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