DWATrust:一种基于“二次加权法”的P2P网络动态综合信任模型

DWATrust:Doubly Weighted Average Based Dynamic Comprehensive Trust Model for P2P Network

针对现有的P2P网络信任模型在聚合节点信任值时对节点行为的差异性与动态性考虑不足,提出了一种基于"二次加权法的"的P2P网络动态综合信任模型——DWATrust。该模型在对节点进行评价时,首先通过引入"时序立体数据表"来记录节点在过去某几段时间内不同评价指标下的评价得分,然后通过"熵值法"分别计算出各个时间段内各个节点对于各个评价指标的不同权值并进行第一次加权综合,得到各个节点在不同时间段内的综合信任值。最后,通过求解一个"非线性规划问题"计算出各个时间段的权值并进行第二次加权综合,得到各个节点在整个时间段上的综合信任值。由此可见,该模型不仅充分考虑到交易上下文及节点上下文的动态变化对节点信任值的影响,而且引入时间粒度来反映这种变化。仿真实验表明,该模型可以较好地识别节点进行周期性振荡欺骗等恶意行为,从而大大改善P2P网络的交易成功率。

According to the existing P2P network＇s deficiency of inadequately considering the difference and the dyna-mic in peers＇ behavior when aggregating peer trust values,a new dynamic comprehensive trust model（DWATrust） was proposed.In this model,a Multi-dimensional Time Series are firstly applied to record evaluations on peers in some past time segments responding to different indexes.Secondly,the different weight for each evaluation index in each time segment is computed by ＂Entropy Method＂ and then the first comprehensive weighted evaluation result in different time segment can be obtained.Finally,the time weight for different time segment can be computed by resolving a nonlinear programming problem and then the second comprehensive weighted evaluation is carried out to obtain the final trust va-lue.Hence,this model not only takes into the consideration that the dynamic changes in transaction context and peer context will influent the peer trust value,but also employs time granularity to reflect the changes.Simulation experiment shows that the model can well identify the malicious peer behavior such as taking strategy to proceed periodic oscillation cheating and then improve the improve transaction success rate.