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Volume 38 Issue 4
Apr.  2016
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XU Jun, ZHONG Yuansheng, WAN Shuping. Incentive Adaptive Trust Model Based on Integrated Intuitionistic Fuzzy Information[J]. Journal of Electronics & Information Technology, 2016, 38(4): 803-810. doi: 10.11999/JEIT150750
Citation: XU Jun, ZHONG Yuansheng, WAN Shuping. Incentive Adaptive Trust Model Based on Integrated Intuitionistic Fuzzy Information[J]. Journal of Electronics & Information Technology, 2016, 38(4): 803-810. doi: 10.11999/JEIT150750

Incentive Adaptive Trust Model Based on Integrated Intuitionistic Fuzzy Information

doi: 10.11999/JEIT150750
Funds:

The National Natural Science Foundation of China (71361012, 61263018), The Science and Technology Project of Jiangxi province educational department of China (GJJ151601), The Colleges Humanities Social Science Research Project of Jiangxi Province (JC1338), The Young Foundation of Jiangxi University of Finance and Economics

  • Received Date: 2015-06-24
  • Rev Recd Date: 2015-12-18
  • Publish Date: 2016-04-19
  • 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.
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