改进的基于推荐证据的对等网络信任模型

Improved trust model based on recommendation evidence for P2P networks

针对传统P2P对等网络信任模型中推荐节点诚实性难以判别的问题,提出了改进的基于推荐证据的P2P网络信任模型。模型根据交易结果,同时更新交易节点和推荐节点的信任记录。采用符合人际交往特性的衰减函数描述信任证据的衰减过程。将D-S证据理论应用于信任模型的信任计算中,将直接证据和推荐证据合成做为信任证据。模型采用基于概率Gossip算法实现信任证据的搜索。试验结果表明:本文算法有效地提高了P2P网络的成功交易率,改善了网络环境。

An improved trust model based on recommendation evidence for P2P network is proposed. The aim of the model is to resolve the problem of identifying dishonesty recommendation peers in traditional trust model for unstructured P2P network. The new model updates the trust records of the transaction node and recommendation nodes simultaneously according to the transaction results. It adopts the decay function, which meets interpersonal characteristics, to describe the decay process of the trust records. The D-S evidence theory is introduced to the computation of the trust model, which integrates direct evidence and recommendation evidence into trust evidence. The model searches trust evidence through probability based Gossip algorithm. The experiment results show that the proposed model can increase the successful transaction rate and improve the network environment.