WSN Network Node Malicious Intrusion Detection Method Based on Reputation Score

Junlin Zhang
{"title":"WSN Network Node Malicious Intrusion Detection Method Based on Reputation Score","authors":"Junlin Zhang","doi":"10.13052/jcsm2245-1439.1213","DOIUrl":null,"url":null,"abstract":"Wireless sensor network (WSN) is the Internet of Things by a large number of sensors in the external physical environment to obtain data information, and use wireless communication technology to provide users with information transmission services. At this stage, communication and security mechanisms are the main problems faced by WSN. This is because most of the existing sensors are powered by batteries with very limited energy, and most of them are deployed in an outdoor open environment, which is easy to be captured as a malicious node. Network attacks. However, the existing malicious node detection methods have shortcomings such as low efficiency, high energy consumption, and insufficient performance. Therefore, this paper proposes a WSN malicious node intrusion detection method based on genetic algorithm optimization of LEACH hierarchical routing protocol. Based on the optimization of the LEACH protocol by genetic algorithm, the method integrates the reputation evaluation mechanism, and screens and eliminates malicious nodes by calculating direct reputation, indirect reputation and comprehensive reputation, thereby ensuring the safe operation of WSN. The simulation results show that this method can effectively resist the attack of malicious nodes on WSN, and has obvious advantages over other methods.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"1 1","pages":"55-76"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cyber Security and Mobility","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13052/jcsm2245-1439.1213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 2

Abstract

Wireless sensor network (WSN) is the Internet of Things by a large number of sensors in the external physical environment to obtain data information, and use wireless communication technology to provide users with information transmission services. At this stage, communication and security mechanisms are the main problems faced by WSN. This is because most of the existing sensors are powered by batteries with very limited energy, and most of them are deployed in an outdoor open environment, which is easy to be captured as a malicious node. Network attacks. However, the existing malicious node detection methods have shortcomings such as low efficiency, high energy consumption, and insufficient performance. Therefore, this paper proposes a WSN malicious node intrusion detection method based on genetic algorithm optimization of LEACH hierarchical routing protocol. Based on the optimization of the LEACH protocol by genetic algorithm, the method integrates the reputation evaluation mechanism, and screens and eliminates malicious nodes by calculating direct reputation, indirect reputation and comprehensive reputation, thereby ensuring the safe operation of WSN. The simulation results show that this method can effectively resist the attack of malicious nodes on WSN, and has obvious advantages over other methods.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于信誉评分的WSN网络节点恶意入侵检测方法
无线传感器网络(WSN)是物联网由大量传感器在外部物理环境中获取数据信息,并利用无线通信技术为用户提供信息传输服务。现阶段,无线传感器网络面临的主要问题是通信机制和安全机制。这是因为现有的传感器大多是由能量非常有限的电池供电,而且大多部署在室外开放环境中,很容易被捕获为恶意节点。网络攻击。然而,现有的恶意节点检测方法存在效率低、能耗高、性能不足等缺点。为此,本文提出了一种基于LEACH分层路由协议遗传算法优化的WSN恶意节点入侵检测方法。该方法在遗传算法优化LEACH协议的基础上,集成了声誉评估机制,通过计算直接声誉、间接声誉和综合声誉来筛选和消除恶意节点,从而保证WSN的安全运行。仿真结果表明,该方法能够有效抵御WSN上恶意节点的攻击,与其他方法相比具有明显的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Cyber Security and Mobility
Journal of Cyber Security and Mobility Computer Science-Computer Networks and Communications
CiteScore
2.30
自引率
0.00%
发文量
10
期刊介绍: Journal of Cyber Security and Mobility is an international, open-access, peer reviewed journal publishing original research, review/survey, and tutorial papers on all cyber security fields including information, computer & network security, cryptography, digital forensics etc. but also interdisciplinary articles that cover privacy, ethical, legal, economical aspects of cyber security or emerging solutions drawn from other branches of science, for example, nature-inspired. The journal aims at becoming an international source of innovation and an essential reading for IT security professionals around the world by providing an in-depth and holistic view on all security spectrum and solutions ranging from practical to theoretical. Its goal is to bring together researchers and practitioners dealing with the diverse fields of cybersecurity and to cover topics that are equally valuable for professionals as well as for those new in the field from all sectors industry, commerce and academia. This journal covers diverse security issues in cyber space and solutions thereof. As cyber space has moved towards the wireless/mobile world, issues in wireless/mobile communications and those involving mobility aspects will also be published.
期刊最新文献
Network Malware Detection Using Deep Learning Network Analysis An Efficient Intrusion Detection and Prevention System for DDOS Attack in WSN Using SS-LSACNN and TCSLR Update Algorithm of Secure Computer Database Based on Deep Belief Network Malware Cyber Threat Intelligence System for Internet of Things (IoT) Using Machine Learning Deep Learning Based Hybrid Analysis of Malware Detection and Classification: A Recent Review
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1