基于阈值自适应控制的VANET智能恶意和自私节点检测

C. A. Kerrache, Abderrahmane Lakas, N. Lagraa
{"title":"基于阈值自适应控制的VANET智能恶意和自私节点检测","authors":"C. A. Kerrache, Abderrahmane Lakas, N. Lagraa","doi":"10.1109/ICEDSA.2016.7818492","DOIUrl":null,"url":null,"abstract":"Detecting malicious and selfish nodes is an important task in Vehicular Adhoc NETworks (VANETs). Various proposals adopted trust management as an alternative solution for it is less costly in terms of computation delay and mobility adaptation, compared to the cryptography-based solutions. However, the existing solutions assume that in general the attackers have always a dishonest behavior that persists over time. This assumption may be misleading, as the attackers can behave intelligently to avoid being detected. In this paper we propose a new solution for the detection of intelligent malicious behaviors based on the adaptive detection threshold. In addition to the detection of malicious nodes, our solution incite attackers to behave well since any malicious behavior will be immediately detected thanks to the adaptive detection threshold. We present simulations results which show the high efficiency of our proposal at ensuring high ratios for both detection and packet delivery.","PeriodicalId":247318,"journal":{"name":"2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Detection of intelligent malicious and selfish nodes in VANET using threshold adaptive control\",\"authors\":\"C. A. Kerrache, Abderrahmane Lakas, N. Lagraa\",\"doi\":\"10.1109/ICEDSA.2016.7818492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Detecting malicious and selfish nodes is an important task in Vehicular Adhoc NETworks (VANETs). Various proposals adopted trust management as an alternative solution for it is less costly in terms of computation delay and mobility adaptation, compared to the cryptography-based solutions. However, the existing solutions assume that in general the attackers have always a dishonest behavior that persists over time. This assumption may be misleading, as the attackers can behave intelligently to avoid being detected. In this paper we propose a new solution for the detection of intelligent malicious behaviors based on the adaptive detection threshold. In addition to the detection of malicious nodes, our solution incite attackers to behave well since any malicious behavior will be immediately detected thanks to the adaptive detection threshold. We present simulations results which show the high efficiency of our proposal at ensuring high ratios for both detection and packet delivery.\",\"PeriodicalId\":247318,\"journal\":{\"name\":\"2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA)\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEDSA.2016.7818492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEDSA.2016.7818492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

摘要

检测恶意和自私节点是车载自组网(vanet)中的重要任务。与基于密码学的解决方案相比,信任管理在计算延迟和移动性适应方面的成本更低,因此各种建议采用信任管理作为替代解决方案。然而,现有的解决方案通常假设攻击者总是有不诚实的行为,并持续一段时间。这种假设可能具有误导性,因为攻击者可以通过智能行为来避免被检测到。本文提出了一种基于自适应检测阈值的智能恶意行为检测新方案。除了检测恶意节点外,我们的解决方案还可以激发攻击者的良好行为,因为任何恶意行为都会立即被检测到,这得益于自适应检测阈值。我们给出的仿真结果表明,我们的方案在保证检测和数据包传输的高比率方面具有很高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Detection of intelligent malicious and selfish nodes in VANET using threshold adaptive control
Detecting malicious and selfish nodes is an important task in Vehicular Adhoc NETworks (VANETs). Various proposals adopted trust management as an alternative solution for it is less costly in terms of computation delay and mobility adaptation, compared to the cryptography-based solutions. However, the existing solutions assume that in general the attackers have always a dishonest behavior that persists over time. This assumption may be misleading, as the attackers can behave intelligently to avoid being detected. In this paper we propose a new solution for the detection of intelligent malicious behaviors based on the adaptive detection threshold. In addition to the detection of malicious nodes, our solution incite attackers to behave well since any malicious behavior will be immediately detected thanks to the adaptive detection threshold. We present simulations results which show the high efficiency of our proposal at ensuring high ratios for both detection and packet delivery.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Noise robust speech recognition using parallel model compensation and voice activity detection methods Analysis and design of MIMO antenna for UWB applications based on the super-formula A comparative study up to 1024 bit Euclid's GCD algorithm FPGA implementation and synthesizing On-line measurement of biomass using colloid dielectric probe and open-ended cell. Determination of the aggregation threshold Classification of ECG signals of normal and abnormal subjects using common spatial pattern
×
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