A Comprehensive and Adaptive Trust Model for Large-Scale P2P Networks |
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Authors: | Xiao-Yong Li Xiao-Lin Gui |
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Affiliation: | Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China |
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Abstract: | Based on human psychological cognitive behavior, a Comprehensive and Adaptive Trust (CAT) model for large-scale P2P networks
is proposed. Firstly, an adaptive trusted decision-making method based on HEW (Historical Evidences Window) is proposed, which
can not only reduce the risk and improve system efficiency, but also solve the trust forecasting problem when the direct evidences
are insufficient. Then, direct trust computing method based on IOWA (Induced Ordered Weighted Averaging) operator and feedback
trust converging mechanism based on DTT (Direct Trust Tree) are set up, which makes the model have a better scalability than
previous studies. At the same time, two new parameters, confidence factor and feedback factor, are introduced to assign the
weights to direct trust and feedback trust adaptively, which overcomes the shortage of traditional method, in which the weights
are assigned by subjective ways. Simulation results show that, compared to the existing approaches, the proposed model has
remarkable enhancements in the accuracy of trust decision-making and has a better dynamic adaptation capability in handling
various dynamic behaviors of peers. |
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Keywords: | |
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