融合采纳函数的动态信任度测模型

从网格的分布性、动态性和不确定性等特征出发,借鉴人类社会主观信任关系的概念,提出了一种新的信任评估模型与方法.该模型引入了采纳函数,区分了节点的反馈可信度和服务可信度,给出了反馈可信度与采纳强度的映射关系,动态调整了对具有不同推荐信任度的第三方实体所推荐信息的不同采信程度,提高了推荐信息的精确度.将采纳强度映射为等效的推荐信任的权重,给出了一个基于动态信任权重的综合信任度计算新方法.仿真实验结果表明,基于采纳函数的动态信任评估方法具有抑制恶意节点的策略性欺骗和不诚实推荐的能力,同时还体现出良好的动态适应性.

Dynamic Trust Measurement and Prediction Model Merging Adoption Function

By analyzing the grid characteristics and referring to the social trust relationship,it proposes a new trust evaluation model and method that introduces an adoption function,make a distinction between the credibility of feedback of a peer and that of service of the peer and gives the mapping relationship of the adoption weight with the robust feedback credibility which adjusts dynamic the degree of adoption for the various recommended information from different third-party entities and increases the accuracy of recommendation information.At the same time,the model comes up with a new method of calculating the total trust based on dynamic weight factors by the mapping of the adaption intensity into the equal weight factor of recommendation trust.Simulation experiments show that the dynamic trust model based on the adoption function can inhibit malicious nodes in strategy deception and dishonesty recommendation and also reflects a good dynamic adaptability.