一种基于Bayes估计的WSN节点信任度计算模型

Trust Computation Model of Nodes Based on Bayes Estimation in Wireless Sensor Networks

鉴于传统网络安全策略无法阻止或识别传感器网络内部节点的攻击或异常行为,结合节点资源受限的特点,提出了一种无线传感器网络节点信任度计算模型。该模型采用Bayes估计方法,通过求解基于Beta分布的节点行为信誉函数的期望值得到直接信任并将其作为Bayes估计的先验信息,将来自邻居节点的推荐信息作为其样本信息。仿真实验表明,本方案有较好的稳定性,能够有效识别异常节点,从而阻止内部节点对网络的攻击,与RFSN相比,不仅节约了存储空间、运算时间与通信量,而且能够避免恶评现象对节点信任度计算的影响。

Traditional network security policy can not prevent attack or identify abnormal behavior of the internal nodes in the sensor network. This paper presented a trust computation model of nodes based on Bayes estimation in wireless sensor networks（Abbreviates as TCM-BE） according to the node resource-constrained characteristics. The direct trust which calculates the expectations of the reputation function on nodes behavior based on beta distribution is priori infor- mation and the recommendation information from neighbor nodes as sample information in Bayes estimation method. The simulation shows that the scheme has good stability, can effectively identify abnormal node, thereby can prevent at-tack from the internal nodes of the network. The analysis shows that compared with RFSN scheme it not only can save storage space and computing time with traffic, but also can avoid the phenomenon of malicious evaluation on the node trnst.