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

Abstract

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.

New Combined Weighting Model Based on Maximizing the Difference in Evaluation Results and Its Application

“…( 3) be the variation coefficient weight of the th index, the variation coefficient of the th index, the standard deviation of the th index, the total number of index, and the mean value of all samples of the th index. Thus, the variation coefficient weight of the th index is calculated using the following [21]:…”

“…The combined weight * , shown in Table 3, Column 11, is obtained by substituting 1 = 0.201, 2 = 0.105, 3 = 0.327, 4 = 0.367, G1 weight (1) from Column 5, G2 weight (2) from Column 7, variation coefficient weight (3) from Column 9, and deviation weight (4) from Column 10 of Table 3 into (21).…”