F-RouND:基于雾的车辆自组织网络流氓节点检测

Anirudh Paranjothi, Mohammed Atiquzzaman, Mohammad S. Khan
{"title":"F-RouND:基于雾的车辆自组织网络流氓节点检测","authors":"Anirudh Paranjothi, Mohammed Atiquzzaman, Mohammad S. Khan","doi":"10.1109/GLOBECOM42002.2020.9322131","DOIUrl":null,"url":null,"abstract":"Vehicular ad hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The rogue nodes in VANETs broadcast malicious information leading to potential hazards, including the collision of vehicles. Previous researchers used either cryptography, trust values, or past vehicle data to detect rogue nodes, but they suffer from high processing delay, overhead, and false-positive rate (FPR). We propose fog-based rogue nodes detection (F-RouND), a fog computing scheme, which dynamically creates a fog utilizing the on-board units (OBUs) of all vehicles in the region for rogue nodes detection. The novelty of F-RouND lies in providing low processing delays and FPR at high vehicle densities. The performance of our F-RouND framework was carried out with simulations using OMNET ++ and SUMO simulators. Results show that F-RouND ensures 45% lower processing delays, 12% lower overhead, and 36% lower FPR at high vehicle densities compared to existing rogue nodes detection schemes.","PeriodicalId":12759,"journal":{"name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","volume":"152 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"F-RouND: Fog-based Rogue Nodes Detection in Vehicular Ad hoc Networks\",\"authors\":\"Anirudh Paranjothi, Mohammed Atiquzzaman, Mohammad S. Khan\",\"doi\":\"10.1109/GLOBECOM42002.2020.9322131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicular ad hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The rogue nodes in VANETs broadcast malicious information leading to potential hazards, including the collision of vehicles. Previous researchers used either cryptography, trust values, or past vehicle data to detect rogue nodes, but they suffer from high processing delay, overhead, and false-positive rate (FPR). We propose fog-based rogue nodes detection (F-RouND), a fog computing scheme, which dynamically creates a fog utilizing the on-board units (OBUs) of all vehicles in the region for rogue nodes detection. The novelty of F-RouND lies in providing low processing delays and FPR at high vehicle densities. The performance of our F-RouND framework was carried out with simulations using OMNET ++ and SUMO simulators. Results show that F-RouND ensures 45% lower processing delays, 12% lower overhead, and 36% lower FPR at high vehicle densities compared to existing rogue nodes detection schemes.\",\"PeriodicalId\":12759,\"journal\":{\"name\":\"GLOBECOM 2020 - 2020 IEEE Global Communications Conference\",\"volume\":\"152 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GLOBECOM 2020 - 2020 IEEE Global Communications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOBECOM42002.2020.9322131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOBECOM42002.2020.9322131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

车辆特设网络(VANETs)使车辆可以广播信标信息,以确保道路安全。VANETs中的流氓节点广播恶意信息,导致潜在危险,包括车辆碰撞。以前的研究人员使用加密技术、信任值或过去的车辆数据来检测恶意节点,但它们受到高处理延迟、开销和假阳性率(FPR)的影响。我们提出了一种基于雾的流氓节点检测(F-RouND)的雾计算方案,该方案利用区域内所有车辆的车载单元(OBUs)动态创建一个雾来进行流氓节点检测。F-RouND的新颖之处在于在高车辆密度下提供低处理延迟和FPR。利用omnet++和SUMO模拟器对F-RouND框架的性能进行了仿真。结果表明,与现有的流氓节点检测方案相比,F-RouND在高车辆密度下确保处理延迟降低45%,开销降低12%,FPR降低36%。
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
F-RouND: Fog-based Rogue Nodes Detection in Vehicular Ad hoc Networks
Vehicular ad hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The rogue nodes in VANETs broadcast malicious information leading to potential hazards, including the collision of vehicles. Previous researchers used either cryptography, trust values, or past vehicle data to detect rogue nodes, but they suffer from high processing delay, overhead, and false-positive rate (FPR). We propose fog-based rogue nodes detection (F-RouND), a fog computing scheme, which dynamically creates a fog utilizing the on-board units (OBUs) of all vehicles in the region for rogue nodes detection. The novelty of F-RouND lies in providing low processing delays and FPR at high vehicle densities. The performance of our F-RouND framework was carried out with simulations using OMNET ++ and SUMO simulators. Results show that F-RouND ensures 45% lower processing delays, 12% lower overhead, and 36% lower FPR at high vehicle densities compared to existing rogue nodes detection schemes.
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
AirID: Injecting a Custom RF Fingerprint for Enhanced UAV Identification using Deep Learning Oversampling Algorithm based on Reinforcement Learning in Imbalanced Problems FAST-RAM: A Fast AI-assistant Solution for Task Offloading and Resource Allocation in MEC Achieving Privacy-Preserving Vehicle Selection for Effective Content Dissemination in Smart Cities Age-optimal Transmission Policy for Markov Source with Differential Encoding
×
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