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A Dynamic Trust Model Based on Naive Bayes Classifier for Ubiquitous Environments

机译:基于朴素贝叶斯分类器的泛在环境动态信任模型

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摘要

Computational models of trust have been proposed for use in ubiquitous computing environments to decide whether to provide services to requesters which are either unfamiliar with service providers or do not have enough access rights to certain services. Due to the highly dynamic and unpredictable characteristic of ubiquitous environments, the trust model should make trust decision dynamically. In this paper, we introduce a novel Naive Bayes classifier based trust model which can dynamically make trust decision in different situations. The trust evaluation is based on service provider's own prior knowledge in stead of assuming variable weights and pre-defined fixed thresholds. This model is also suitable to make decision when only limited information is available in ubiquitous environments. Finally we give the simulation results of our model and the comparison with the related works.
机译:已经提出了信任的计算模型,用于普遍存在的计算环境中,以决定是否向不熟悉服务提供者或对某些服务没有足够访问权限的请求者提供服务。由于普适环境的高度动态和不可预测的特性,信任模型应该动态地做出信任决策。在本文中,我们介绍了一种新颖的基于朴素贝叶斯分类器的信任模型,该模型可以在不同情况下动态地做出信任决策。信任评估基于服务提供商本身的先验知识,而不是假设可变权重和预定义的固定阈值。当在普适环境中只有有限的信息可用时,该模型也适合做出决策。最后,给出了模型的仿真结果,并与相关工作进行了比较。

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