基于节点信任值的WSNs入侵检测方案

为了保证无线传感器网络(wireless sensor network,WSNs)内部节点入侵检测中具有较高的检测率和较低的误检率,提出了一种基于节点信任值的层簇式WSNs入侵检测方案。该方案通过分析WSNs中典型网络攻击特征,定义了节点的多种典型信任属性,并利用马氏距离判断节点信任属性是否异常来获知节点是否存在异常,最后利用贝塔分布理论和异常折扣因子相结合实现节点信任值的计算和更新,从而实现节点入侵检测判断。经仿真,结果表明该方案可实现常见入侵的检测,具有较高的检测率和较低的误检率。

Intrusion detection scheme based node trust value in WSNs

In order to achieve a higher detection rate and a lower false positive rate of internal nodes intrusion detection in wireless sensor networks (WSNs), an intrusion detection scheme of cluster WSNs based node trust value is proposed. In this scheme, variety of typical trust attributes of nodes are defined by analyzing the typical network attack characteristics in WSNs, and the theory of Mahalanobis distance is used to judge whether the trust attributes are abnormal to determine whether the nodes are abnormal. Finally, the node trust value which is used to judge the intrusion detection is calculated and updated based on the Beta distribution theory combined with the abnormal discount factor. The simulation results show that the scheme can detect common intrusion and has a higher detection rate and a lower false positive rate.