Sinkhole Attack Detection-Based SVM In Wireless Sensor Networks

Sihem Aissaoui, Sofiane Boukli-Hacene
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引用次数: 2

Abstract

Wireless sensor network is a special kind of ad hoc network characterized by high density, low mobility, and the use of a shared wireless medium. This last feature makes the network deployment easy; however, it is prone to various types of attacks such as sinkhole attack, sybil attack. Many researchers studied the effect of such attacks on the network performance and their detection. Classification techniques are some of the most used end effective methods to detect attacks in WSN. In this paper, the authors focus on sinkhole attack, which is one of the most destructive attacks in WSNs. The authors propose an intrusion detection system for sinkhole attack using support vector machines (SVM) on AODV routing protocol. In the different experiments, a special sinkhole dataset is used, and a comparison with previous techniques is done on the basis of detection accuracy. The results show the efficiency of the proposed approach.
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无线传感器网络中基于天坑攻击检测的支持向量机
无线传感器网络是一种特殊的自组织网络,具有高密度、低移动性和使用共享无线介质的特点。最后一个特性使网络部署变得容易;然而,它很容易受到各种类型的攻击,如天坑攻击,sybil攻击。许多研究人员研究了此类攻击对网络性能的影响及其检测方法。分类技术是无线传感器网络中检测攻击最常用的有效方法之一。陷坑攻击是无线传感器网络中最具破坏性的攻击之一。提出了一种基于AODV路由协议的支持向量机(SVM)入侵检测系统。在不同的实验中,使用了一个特殊的天坑数据集,并在检测精度的基础上与以往的技术进行了比较。实验结果表明了该方法的有效性。
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