针对现有无线传感器网络攻击检测算法检测率低、计算复杂度高等问题,提出一种新的基于分簇模型的无线传感器网络攻击检测算法。借鉴集中式数据汇聚模型中二分比较法的思想,对分簇式无线传感器网络中各簇均值进行二分比较,利用两部分均值的残差的统计特性进行攻击检测,并在相同实验条件下对二分比较法和t检验法进行对比分析。仿真结果证明,该算法的攻击检测性能要优于现有的攻击检测算法。
For the low attack detection rate and high computational complexity of the existing attack detection algorithm in wireless sensor networks, a new attack detection method based on clustering is proposed. The method uses the idea of sample halving, by which the halved two parts of the cluster averages are checked against each other. Under the same experimental conditions, the new algorithm is compared with the sample halving and the t-test method. Simulation results show that the performance of the new algorithm is better than the existing attack detection algorithm.