基于支持向量机的无线传感器网络的入侵检测系统

Intrusion detection system for WSNs based on SVM

无线传感器网络入侵检测方法是目前的研究热点。在介绍支持向量机(SVM)原理、无线传感器网络的入侵类型以及不同类型所具有的数据特性的基础上,提出了一种基于SVM的无线传感器网络的入侵检测系统,该系统把网络拓扑分为簇成员、簇头和Sink三层结构,每层均能根据SVM的训练结果进行入侵检测的判断。实验结果表明:该检测系统具有较高的检测率和较低的能量消耗。

Intrusion detection method for wireless sensor networks （WSNs） is current research hot spot. On the basis of introductions of the principle of support vector machine（ SVM）, WSNs intrusion types and characteristics of different types of data, an intrusion detection system for WSNs based on SVM is put forward. This system divides network topology into three layers structure, which are cluster members, cluster header and Sink node, and each layer can execute judgment of intrusion detection according to SVM training results. The experimental results show that the detection system has characteristics of higher detection rate and low energy consumption.