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Mathematical Problems in Engineering
Volume 2015, Article ID 789820, 9 pages
Research Article

Modeling Dynamic Trust and Risk Evaluation Based on High-Order Moments

Yan Gao,1,2 Zhiyong Dai,1,2 and Wenfen Liu1,2

1Zhengzhou Information Science and Technology Institute, Zhengzhou 450001, China
2State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou 450001, China

Received 16 April 2014; Revised 5 August 2014; Accepted 14 August 2014

Academic Editor: Alessandro Palmeri

Copyright © 2015 Yan Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper proposes a dynamic trust and risk evaluation model based on high-order moments. The credibility of an entity is measured with trust degree and risk value comprehensively. Firstly, considering the dynamic and time decay characters of trust, a time attenuation function is defined, and direct trust is further expressed. Subsequently, in order to improve the accuracy of feedback trust, a filter mechanism is constructed to eliminate the false feedback, combining coefficient of skewness with hypothesis test. More importantly, the weights of direct trust and feedback trust are derived subjectively and adaptively with the moments and frequency of direct interactions. Furthermore, risk is evaluated with direct risk and feedback risk, which are obtained by mainly using coefficient of variation and coefficient of kurtosis. Risk value can be used to measure the stability of providing services. Simulation results show that the proposed model not only has high accuracy, but also resists effectively collusive attacks and strategic malicious behaviors.