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目前缺乏有效的方法对已存的各种信任模型进行分析和评估。为解决该问题,提出了一种基于可信建模过程的信任模型评估算法。将信任模型按照信任生命周期分解成信任产生、信任建模、信任计算、信任决策和信任传递这5个部分,对每个过程进行可信性分析,并模糊量化评估值,用Bayesian融合形成综合的评估结果。最后以无线传感器网络信任模型为例,对所提算法进行了验证,同时给出了算法的有效性分析和仿真。结果证明所提算法能解决给定信任模型的最优化选择问题,并在准确性、稳定性和效率3个方面相对以往算法有一定的改善。该评估结果为信任模型的标准化提供了一定的参考。
There is currently no effective way to analyze and evaluate the various trust models that have been put in place. To solve this problem, a trust model evaluation algorithm based on trusted modeling process is proposed. According to the trust life cycle, the trust model is decomposed into five parts: trust generation, trust modeling, trust calculation, trust decision and trust transfer. The credibility of each process is analyzed and the evaluation values are blurred and quantified by Bayesian fusion Assessment results. Finally, taking the wireless sensor network trust model as an example, the proposed algorithm is verified, and the effectiveness analysis and simulation of the algorithm are given. The results show that the proposed algorithm can solve the optimal selection problem of a given trust model and improve the accuracy, stability and efficiency compared with the previous algorithms. The result of the assessment provides some reference for the standardization of trust model.