Incentive adaptive trust model based on integrated Intuitionistic Fuzzy Information

被引：0
|
作者：
Xu J. [1 ,2 ]
Zhong Y. [2 ]
Wan S. [2 ]
机构：
[1] College of Modern Economics & Management, Jiangxi University of Finance and Economics, Nanchang
[2] College of Information Technology, Jiangxi University of Finance and Economics, Nanchang
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2016年 / 38卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Distributed network; Intuitionistic Fuzzy Information (IFI); Recommendation credibility; Trust model;
D O I：
10.11999/JEIT150750
中图分类号：
学科分类号：
摘要：
Existing trust models can not effectively express the uncertainty of trust relationship and deal with such issues as dishonest feedbacks and strategic frauds from malicious entities in the distributed network, an adaptive trust model based on aggregating Intuitionistic Fuzzy Information (IFI) is proposed. Firstly, in order to incentivize entities providing trustworthy service and punish entities taking along malicious behavior, an approach on aggregating IFI is constructed to compute the direct trust intuitionistic fuzzy numbers which contain the latest permanence factor and the time decay factor. Then, the recommendation credibility and uniformity are defined to detect dishonest recommendation. Subsequent, an adaptive weighted approach is developed to avoid distributing the weights of direct and indirect trust subjectively. The simulation experiments demonstrate that the proposed model not only is robust on malicious attacks, but also has better adaptability and effectiveness. © 2016, Science Press. All right reserved.
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页码：803 / 810
页数：7
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