CBTM: A Trust Model with Uncertainty Quantification and Reasoning for Pervasive Computing
CBTM: A Trust Model with Uncertainty Quantification and Reasoning for Pervasive Computing
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DOI：
10.1007/11576235_56
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发表时间：
2005-11
期刊：
影响因子：
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通讯作者：
Rui He;J. Niu;Guangwei Zhang
中科院分区：
文献类型：
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作者：
Rui He;J. Niu;Guangwei Zhang
本文提出了一种新的信任模型，在信任模型中，我们基于一个外来的不确定性理论，即云模型。我们把实体之间的信任看作是一片云，称之为信任云。基于这样一个信任量化模型，我们进一步提出了普适计算环境中信任推理所需的传播信任关系和聚合信任关系的计算算法。最后，通过仿真实验将本文提出的信任模型与其他三种典型的信任模型进行了比较，结果表明基于云的信任模型在总体上具有更好的性能。
This paper presents a novel trust model in which we model trust based on an exotic uncertainty theory, namely cloud model. We regard trust between entities as a cloud that is called as trust cloud. Based on such a quantification model of trust, we further propose the algorithms to compute propagated trust relationships and aggregated trust relationships, which are needed for trust reasoning in pervasive computing environments. Finally, we compare the proposed trust model with other three typical models in simulation experiments, and the results shows the cloud-based trust model performs better in a total sense.