一种可信网络中敏感的直接信任度计算模型

Sensitive direct trust computation model for trusted networks

借鉴人类信任关系的遗忘、衰减、相对稳定又动态敏感、敏感性的非对称性和空时联合等特征,提出一种具有双滑动窗口机制的敏感的直接信任度计算模型。采用一较大的稳定性窗口获取直接信任度的稳定性部分,采用一较小的敏感性窗口获取其敏感性部分。在敏感性窗口内,分别采用非对称地提高负向波动的交易满意度权重方法和自适应地改变窗口大小的方法,刻画直接信任度对交易满意度波动的空时联合特征。仿真实验表明,所提出的直接信任度模型既相对稳定又对节点行为变化单边动态敏感,且这种敏感性具有明显的空时联合特性。

Learning from features of human trust relationship such as forgetting,attenuation,relatively stable but dynamically sensitive,asymmetry and united space-time features of sensitivity,this paper proposed a direct trust computation model（DTD） based on a moving two-windowed mechanism.It adopted a wide stability window to obtain the stable part of DTD.It adopted a small sensitivity window to obtain the sensitive part of DTD.In the sensitivity window,it used two methods to describe the united space-time feature for variations of DTD to those of transaction satisfaction degree（TSD）.On the one hand,asymmetrically set TSDs negatively changed with high weights.On the other hand,dynamically and adaptively changed the window’s width.Experiment results show that the proposed DTD model can maintain to be relatively stable but sensitive to minus variation of node behavior,and the sensitivity has a united space-time feature.