{"title":"Sinkhole Attack Detection-Based SVM In Wireless Sensor Networks","authors":"Sihem Aissaoui, Sofiane Boukli-Hacene","doi":"10.4018/IJWNBT.2021070102","DOIUrl":null,"url":null,"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.","PeriodicalId":422249,"journal":{"name":"Int. J. Wirel. Networks Broadband Technol.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Wirel. Networks Broadband Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJWNBT.2021070102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.