{"title":"基于最小事件周期计算方法的无线传感器网络恶意节点检测","authors":"J. Priyanka, S. Tephillah, A. Balamurugan","doi":"10.1109/ICCSP.2014.6949975","DOIUrl":null,"url":null,"abstract":"Wireless sensor networks consists of a large number of Tiny low power sensor nodes, each with sensing, computation and wireless communication capabilities. Sensor nodes are deployed in unattended environments, they are vulnerable to a wide variety of attacks. Malicious nodes can generate incorrect readings and misleading reports. In this paper, we present a malicious node detection scheme for wireless sensor networks. The malicious nodes are detected by computing the average number of event cycles. In addition, each sensor node maintains the trust values of its neighbouring nodes to reflect their behaviour in decision-making. Computer simulation shows that the proposed scheme achieves high malicious node detection accuracy with lesser number of event cycles to detect the malicious node.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Malicious node detection using minimal event cycle computation method in wireless sensor networks\",\"authors\":\"J. Priyanka, S. Tephillah, A. Balamurugan\",\"doi\":\"10.1109/ICCSP.2014.6949975\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless sensor networks consists of a large number of Tiny low power sensor nodes, each with sensing, computation and wireless communication capabilities. Sensor nodes are deployed in unattended environments, they are vulnerable to a wide variety of attacks. Malicious nodes can generate incorrect readings and misleading reports. In this paper, we present a malicious node detection scheme for wireless sensor networks. The malicious nodes are detected by computing the average number of event cycles. In addition, each sensor node maintains the trust values of its neighbouring nodes to reflect their behaviour in decision-making. Computer simulation shows that the proposed scheme achieves high malicious node detection accuracy with lesser number of event cycles to detect the malicious node.\",\"PeriodicalId\":149965,\"journal\":{\"name\":\"2014 International Conference on Communication and Signal Processing\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Communication and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2014.6949975\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Communication and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSP.2014.6949975","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Malicious node detection using minimal event cycle computation method in wireless sensor networks
Wireless sensor networks consists of a large number of Tiny low power sensor nodes, each with sensing, computation and wireless communication capabilities. Sensor nodes are deployed in unattended environments, they are vulnerable to a wide variety of attacks. Malicious nodes can generate incorrect readings and misleading reports. In this paper, we present a malicious node detection scheme for wireless sensor networks. The malicious nodes are detected by computing the average number of event cycles. In addition, each sensor node maintains the trust values of its neighbouring nodes to reflect their behaviour in decision-making. Computer simulation shows that the proposed scheme achieves high malicious node detection accuracy with lesser number of event cycles to detect the malicious node.