An evaluation management mechanism based on node trust

Jing Huang, Zhe Sun, Hui-Juan Zhang, Jia Chen, Shen He
{"title":"An evaluation management mechanism based on node trust","authors":"Jing Huang, Zhe Sun, Hui-Juan Zhang, Jia Chen, Shen He","doi":"10.1109/ICCSS53909.2021.9721966","DOIUrl":null,"url":null,"abstract":"Tens of billions of nodes in the Internet of Things work together, making the boundary between virtual and reality more and more blurred. However, while the Internet age has brought subversive changes to people's lives, it has also brought huge security risks. Therefore, in order to effectively identify malicious nodes and realize the security and credibility of each node in the Internet of Things, this paper proposes an evaluation and management mechanism based on node trust. First, perform direct trust measurement of nodes based on node satisfaction and reliability stored locally; Secondly, the indirect trustworthiness measurement of the node is realized by combining the direct recommendation trust degree and the indirect recommendation trust degree; Finally, according to the comprehensive trust value, it dynamically analyzes the risk and threat of the environment where the node is located, and identifies and eliminates malicious nodes in time. The simulation results show that the evaluation management mechanism proposed in this paper can effectively identify malicious nodes, thereby ensuring the security of the Internet of Things.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"2 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSS53909.2021.9721966","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Tens of billions of nodes in the Internet of Things work together, making the boundary between virtual and reality more and more blurred. However, while the Internet age has brought subversive changes to people's lives, it has also brought huge security risks. Therefore, in order to effectively identify malicious nodes and realize the security and credibility of each node in the Internet of Things, this paper proposes an evaluation and management mechanism based on node trust. First, perform direct trust measurement of nodes based on node satisfaction and reliability stored locally; Secondly, the indirect trustworthiness measurement of the node is realized by combining the direct recommendation trust degree and the indirect recommendation trust degree; Finally, according to the comprehensive trust value, it dynamically analyzes the risk and threat of the environment where the node is located, and identifies and eliminates malicious nodes in time. The simulation results show that the evaluation management mechanism proposed in this paper can effectively identify malicious nodes, thereby ensuring the security of the Internet of Things.
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
基于节点信任的评价管理机制
物联网中数百亿节点协同工作,使得虚拟与现实的界限越来越模糊。然而,互联网时代在给人们的生活带来颠覆性变化的同时,也带来了巨大的安全隐患。因此,为了有效识别恶意节点,实现物联网中每个节点的安全与可信,本文提出了一种基于节点信任的评估与管理机制。首先,基于存储在本地的节点满意度和可靠性对节点进行直接信任度量;其次,结合直接推荐信誉度和间接推荐信誉度实现节点的间接可信度度量;最后,根据综合信任值动态分析节点所在环境的风险和威胁,及时识别和消除恶意节点。仿真结果表明,本文提出的评估管理机制能够有效识别恶意节点,从而保障物联网的安全。
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
自引率
0.00%
发文量
0
期刊最新文献
Research on the Prediction Model of Key Personnel's Food Crime Based on Stacking Model Fusion A Multidimensional System Architecture Oriented to the Data Space of Manufacturing Enterprises Semi-Supervised Deep Clustering with Soft Membership Affinity Moving Target Shooting Control Policy Based on Deep Reinforcement Learning Prediction of ship fuel consumption based on Elastic network regression model
×
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