CCTB:普适环境下信任引导的上下文相关性

Sheikh Iqbal Ahamed, Mehrab Monjur, M. S. Islam
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引用次数: 10

摘要

在普适计算环境中的手持设备在发现、共享和访问服务和内容时,容易出现安全问题和侵犯隐私问题。建立信任模式就是为了打击这种违规行为。虽然初始信任分配是发展整体信任的一个重要问题,但迄今为止这方面的研究还很少。在普遍的智能空间中,相似类型的上下文彼此之间表现出显著的相关性。然而,在计算初始信任值时没有考虑到这一事实。在本文中,我们描述了一种分配初始信任的新机制:CCTB (Context Correlation for trust Bootstrapping),它利用了上下文本体中不同上下文之间存在的相关性。我们通过模拟两种不同的场景来评估CCTB的有效性。我们证明,CCTB提供了比这里考虑的其他模型更好的初始信任值。我们还使用。net Compact Framework实现了一个性能度量的原型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CCTB: Context Correlation for Trust Bootstrapping in Pervasive Environment
Handheld devices in a pervasive computing environment are prone to security as well as privacy violations, while discovering, sharing and accessing services and contents. Trust models are devised to fight against such violations and breaches. Although initial trust assignment is an important issue in evolving overall trust, a little amount of work has been done in this field so far. In pervasive smart space, similar type of contexts exhibits significant correlations to each other. However, this fact is not taken into consideration while computing the initial trust values. In this paper, we describe a new mechanism to assign initial trust: CCTB (Context Correlation for Trust Bootstrapping), which takes advantage of the presence of correlations among different contexts in a context-ontology. We evaluate the effectiveness of CCTB by simulating in two different scenarios. We show that CCTB offers better initial trust values than the other models considered here. We also implement a prototype for performance measurement using .NET Compact Framework.
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