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A Comprehensive Trust Model Based on Reputation and Fuzzy Theory

机译:基于声誉和模糊理论的全面信任模式

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—In Ubiquitous Network, the core problem is how heterogeneous terminals communicate credibly between each other. We will achieve communication and “Ubiquitous” between varieties of heterogeneous terminals only if more reliable interaction through heterogeneous terminals could be made. This paper puts present a Comprehensive Trust Model based on Reputation and Fuzzy subsystems (CFMBRF), indirect recommending trust calculation method of the model adopts the “an fuzzy based credibility evaluation method for indirect trust computation”, then on the basis of the model based on reputation, import the fuzzy inference subsystems, it is able to handle subjective concept such as " importance of a interaction", "the decisions in the uncertainty region " and "setting the result of interaction ", can humanistic make decision about uncertain problem. This paper simulates the network having no-fuzzy subsystem and network which have the fuzzy subsystem, makes comparison between the two networks, tests overhead and stability of the CFMBRF. It can be seen that the network using the fuzzy subsystem greatly increased the validity of the interaction, decreased the number of query for the reputation vector, and proved the effectiveness of the CFMBRF model.
机译:- 普遍存在的网络,核心问题是异构终端如何彼此之间可信地通信。只有通过异构终端的更可靠的相互作用,我们将在多均终端的各种终端之间实现沟通和“无处不在”。本文提出了一种基于声誉和模糊子系统(CFMBRF)的全面信任模型,该模型的间接推荐信任计算方法采用“间接信托计算的模糊可信度评估方法”,然后基于基于模型的模型声誉,导入模糊推理子系统,它能够处理主观概念,如“相互作用的重要性”,“不确定区域的决定”和“设置互动结果”,可以人文决定不确定问题。本文模拟了具有模糊子系统的无模糊子系统和网络的网络,在两个网络之间进行比较,测试CFMBRF的开销和稳定性。可以看出,使用模糊子系统的网络大大增加了交互的有效性,降低了声誉向量的查询数量,并证明了CFMBRF模型的有效性。

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