Trust quantitative model with multiple decision factors in trusted network

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.