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基于平衡迭代规约层次聚类的无线传感器网络流量异常检测方案
引用本文:郁滨,熊俊.基于平衡迭代规约层次聚类的无线传感器网络流量异常检测方案[J].电子与信息学报,2022,44(1):305-313.
作者姓名:郁滨  熊俊
作者单位:战略支援部队信息工程大学 郑州 450000
基金项目:信息保障技术重点实验室开放基金(KJ-15-104)
摘    要:针对现有网络流量异常检测方法不适用于实时无线传感器网络(WSN)检测环境、缺乏合理异常判决机制的问题,该文提出一种基于平衡迭代规约层次聚类(BIRCH)的WSN流量异常检测方案.该方案在扩充流量特征维度的基础上,利用BIRCH算法对流量特征进行聚类,通过设计动态簇阈值和邻居簇序号优化BIRCH聚类过程,以提高算法的聚类...

关 键 词:无线传感器网络  流量异常检测  特征维度扩充  基于平衡迭代规约层次聚类  拐点
收稿时间:2020-11-30

A Novel WSN Traffic Anomaly Detection Scheme Based on BIRCH
YU Bin,XIONG Jun.A Novel WSN Traffic Anomaly Detection Scheme Based on BIRCH[J].Journal of Electronics & Information Technology,2022,44(1):305-313.
Authors:YU Bin  XIONG Jun
Affiliation:Information Engineering University, PLA Strategic Support Force, Zhengzhou 450000, China
Abstract:For the problems that the existing network traffic anomaly detection methods are not suitable for the real-time WSN (Wireless Sensor Networks) and lack reasonable decision mechanisms, a novel Wireless Sensor Networks (WSN) traffic anomaly detection scheme based on BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) is proposed. Based on expanding the dimension of traffic characteristics, the scheme uses BIRCH algorithm to cluster traffic characteristics. By introducing the dynamic cluster threshold and neighbor cluster serial numbers, the BIRCH process is optimized to improve the clustering quality and performance robustness. Furthermore, to ensure the detection accuracy of the scheme, a comprehensive decision mechanism based on turning point is designed to detect abnormal traffic, combined with prediction and clustering results. The experimental results show that the proposed scheme has obvious advantages in detection effect and stability of detection performance.
Keywords:Wireless Sensor Networks (WSN)  Traffic anomaly detection  Characteristic dimension expansion  Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH)  Turning point
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