Chinese Journal of Computers   Full Text
Title	Trust Quantitative Model with Multiple Decision Factors in Trusted Network`
Authors	LI Xiao-Yong GUI Xiao-Lin
Address	(School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049)
Year	2009
Issue	No.3(405—416)
Abstract &   Background	Abstract In a trustworthy network system, trust model is one of the most complex concepts in social relationships, and it also is an abstract psychological cognitive process, involving assumptions, expectations, behavior and the environment, and other factors. So, it is very difficult to quantify and forecast trust-ship accurately. In this paper, a novel dynamic trust quantization model with multiple decision factors based on information entropy is proposed, in which multiple decision factors, including direct trust, trust risk function, feedback trust, incentive function and active degree, are incorporated to reflect trust relationship’s complexity and uncertainty in various angles. Also, the weight of classification is set up by information entropy theory for these decision factors, which overcomes the shortage of traditional method, in which the weight is set up by subjective manners, and makes the model has a better rationality and a higher practicability. Simulation’s results show that, compared to the existing trust quantization metrics, the model in this paper is more robust on trust dynamic adaptability, has remarkable enhancements in the system’s security. Keywords trustworthy network; trust quantitative model; information entropy; multiple decision factors Background With the widespread applications of large-scale open environments, such as Grid computing, Ubiquitous computing, P2P computing, Ad hoc networks, etc., the technology of dynamic trust management has become a significant requirement from a network economics’ point of view, and trust evaluating and predicting mechanism has become a determining factor for any given service’s success. But the dynamic nature of trust creates the biggest challenge in measuring trust value and predicting trust relationship amongst peers. In recent years, many of state-of-the-art trust models have been proposed, and some of them are very innovative and elaborate, but most of the studies still have some limitations: (1) Many current trust models use simple or one-sided trust decision factors to quantify and predict trustworthiness of service providers or requesters, which may lead to inaccurate or unfair outcome of trust decision. When trust relationship between peers cannot be fairly defined, it is unstable, and difficult to manage and predict. (2) In many of previous studies, the subjective assigning method to weights of trust decision factors cannot reflect trust decision scientific and reasonable, and may lead to misjudgment of trust decision result. Focusing on these problems, in this paper, a novel dynamic trust quantization model with multiple decision factors based on information entropy is proposed, in which multiple decision factors, including direct trust, trust risk function, feedback trust, incentive function and active degree, are incorporated to reflect trust relationship’s complexity and uncertainty in various angles. Also, the weight of classification is set up by information entropy theory for these decision factors, which overcomes the shortage of traditional method, in which the weight is set up by subjective manners, and makes the model has a better rationality and a higher practicability. Simulation’s results show that, compared to the existing trust quantization metrics, the model in this paper is more robust on trust dynamic adaptability, has remarkable enhancements in the system’s security. This work is supported by the National Nature Science Foundation of China (No.60873071); the National High-Tech Research and Development Plan of China(863) (No.2008AA01Z410); Program for New Century Excellent Talents in University of China (NCET No.05-0829); Scientific and Technological Project in Shaanxi Province, China (No.2007K04-05).