一种基于个体经验的多粒度信任模型

Multi-granularity Trust Model Based on Individual Expericence

分布式网络中,对于某一节点所提供的相同质量的服务,不同的访问节点对该节点的信任评价存在差异。导致这种差异的原因,一方面与访问节点的直接交互经验有关,另一方面与访问节点的兴趣爱好及对服务评价的理解角度有关(有的节点对服务的评价看重的是下载速度,而有的节点则更看重服务的安全可靠等),这种差异必然影响信任评价的准确性。为了消除个体节点信任评价差异所产生的影响,通过引入经验因子的方法和采用多元组的信任信息记录方法,提出了一种基于个体经验的多粒度信任模型。实验分析表明,该模型在信任评价的粒度、信任评价的准确性等方面有较大的提高。

In distributed networks, the trust evaluation for the same quality services of one node conducted by different access nodes is different. On the one side,it has relation to the direct mutual experience of the accessing node. And on the other side, it has relation to the accessing node＇s interest and opinion about the service evaluation. Some nodes think a lot of the download speed, while some other nodes put more emphasis on the security and reliability of the service, which cannot but lead to influence the veracity of trust evaluation. In order to eliminate the infection resulted from the trust evaluation difference of individual nodes, a multi-granularity trust model based on individual experience was put forward. In this model, experience factor and multi trust information recording methods were employed. Experiment and analysis show that the proposed model has better improvement in granularity and veracity of trust evaluation.