集成直觉模糊信息的主观信任模型

针对复杂的在线服务环境下存在的主观性和不确定性,且缺乏从信任程度、不信任程度和不确定性程度三方面描述信任的方法,提出一种集成直觉模糊信息的主观信任模型。首先,给出了一种改进的集成精确数为直觉模糊数的方法,并结合K均值聚类算法,计算实体的直接信任和间接信任;然后,根据基于直觉模糊熵的权重分配策略计算综合信任;最后进行了仿真实验验证。结果表明该方法能有效抑制信用欺诈行为,且当恶意节点达到35%的情况下仍然维持一个较低的误差水平。

Subjective trust model based on integrated intuitionistic fuzzy information

Aiming at the subjectivity and uncertainty of online service environment, as well as existing trust models cannot describe trust degree, distrust degree and uncertainty degree, simultaneously, a subjective trust model based on intuitionistic fuzzy information was proposed. Firstly, an improved approach for aggregating crisp values into Intuitionistic Fuzzy Numbers (IFN) was developed. Then, based on this approach, the direct trust IFN and the indirect trust IFN could be calculated. Furthermore, the final trust was obtained by utilizing weight distribution strategy based on intuitionstic fuzzy entropy. The experimental results demonstrate that the proposed model is effective for credit fraud, and maintains low error level when malicious entities ratio reaches 35%.