Peer-to-Peer网络中,为保证系统的整体可用性,节点间的信任评估模型必须被建立起来。现有的模型不能灵活地反映考虑不同影响因素情况下节点的信任值。同时,不能避免FreeRiding现象。论文全面地描述了节点的行为,将激励机制引入信任模型中。同时考虑了影响节点信任值的不同因素,以及他们之间复杂的依赖关系,利用bayesian网络和领域层次结构相结合的方法有效合理地将各方面因素整合起来,形成能够反映节点在不同方面的本地信任值。
In peer-to-peer network,a trust model must be constructed to provide usability.However,almost all existing models do not take different factors into account in building this trust values,and they can not avoid the free riding phenomenon.In this paper,first we describe the node behavior comprehensively,then incorporate incentive mechanism into trust model.We leverage Bayesian network and domain hierarchy to incorporate all the factors to get peer local trust value.