{"title":"基于贝叶斯声誉评估模型的无线传感器网络安全防御策略","authors":"Zhijun Teng, Sian Zhu, Mingzhe Li, Libo Yu, Jinliang Gu, Liwen Guo","doi":"10.1049/cmu2.12700","DOIUrl":null,"url":null,"abstract":"<p>In order to solve the security problems caused by malicious nodes in wireless sensor networks, a TS-BRS reputation model based on time series analysis is proposed in this paper. By using the time series analysis method, the matching analysis of two time series is carried out to reduce the interference of channel conflicts on the reputation evaluation model and improve the accuracy of model recognition. In order to improve the adaptability of the evaluation model, the adaptive maintenance function μ is introduced into the update of credit value, which aggravates the influence of node behaviour on credit value at the present stage. The simulation results show that the new reputation evaluation model can effectively improve the detection rate and detection speed of malicious nodes in the network. After the introduction of maintenance function, the reputation value of the captured malicious nodes in the network has a faster convergence speed.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"18 1","pages":"55-62"},"PeriodicalIF":1.5000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12700","citationCount":"0","resultStr":"{\"title\":\"Wireless sensor network security defense strategy based on Bayesian reputation evaluation model\",\"authors\":\"Zhijun Teng, Sian Zhu, Mingzhe Li, Libo Yu, Jinliang Gu, Liwen Guo\",\"doi\":\"10.1049/cmu2.12700\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In order to solve the security problems caused by malicious nodes in wireless sensor networks, a TS-BRS reputation model based on time series analysis is proposed in this paper. By using the time series analysis method, the matching analysis of two time series is carried out to reduce the interference of channel conflicts on the reputation evaluation model and improve the accuracy of model recognition. In order to improve the adaptability of the evaluation model, the adaptive maintenance function μ is introduced into the update of credit value, which aggravates the influence of node behaviour on credit value at the present stage. The simulation results show that the new reputation evaluation model can effectively improve the detection rate and detection speed of malicious nodes in the network. After the introduction of maintenance function, the reputation value of the captured malicious nodes in the network has a faster convergence speed.</p>\",\"PeriodicalId\":55001,\"journal\":{\"name\":\"IET Communications\",\"volume\":\"18 1\",\"pages\":\"55-62\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.12700\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Communications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/cmu2.12700\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Communications","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cmu2.12700","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Wireless sensor network security defense strategy based on Bayesian reputation evaluation model
In order to solve the security problems caused by malicious nodes in wireless sensor networks, a TS-BRS reputation model based on time series analysis is proposed in this paper. By using the time series analysis method, the matching analysis of two time series is carried out to reduce the interference of channel conflicts on the reputation evaluation model and improve the accuracy of model recognition. In order to improve the adaptability of the evaluation model, the adaptive maintenance function μ is introduced into the update of credit value, which aggravates the influence of node behaviour on credit value at the present stage. The simulation results show that the new reputation evaluation model can effectively improve the detection rate and detection speed of malicious nodes in the network. After the introduction of maintenance function, the reputation value of the captured malicious nodes in the network has a faster convergence speed.
期刊介绍:
IET Communications covers the fundamental and generic research for a better understanding of communication technologies to harness the signals for better performing communication systems using various wired and/or wireless media. This Journal is particularly interested in research papers reporting novel solutions to the dominating problems of noise, interference, timing and errors for reduction systems deficiencies such as wasting scarce resources such as spectra, energy and bandwidth.
Topics include, but are not limited to:
Coding and Communication Theory;
Modulation and Signal Design;
Wired, Wireless and Optical Communication;
Communication System
Special Issues. Current Call for Papers:
Cognitive and AI-enabled Wireless and Mobile - https://digital-library.theiet.org/files/IET_COM_CFP_CAWM.pdf
UAV-Enabled Mobile Edge Computing - https://digital-library.theiet.org/files/IET_COM_CFP_UAV.pdf