SEEK+:通过基于连续仪表盘摄像头的车辆定位框架确保车辆 GPS 安全

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Peng Jiang , Hongyi Wu , Yanxiao Zhao , Dan Zhao , Gang Zhou , Chunsheng Xin
{"title":"SEEK+:通过基于连续仪表盘摄像头的车辆定位框架确保车辆 GPS 安全","authors":"Peng Jiang ,&nbsp;Hongyi Wu ,&nbsp;Yanxiao Zhao ,&nbsp;Dan Zhao ,&nbsp;Gang Zhou ,&nbsp;Chunsheng Xin","doi":"10.1016/j.pmcj.2024.101916","DOIUrl":null,"url":null,"abstract":"<div><p>Nowadays, the Global Positioning System (GPS) plays an critical role in providing navigational services for transportation and a variety of other location-dependent applications. However, the emergent threat of GPS spoofing attacks compromises the safety and reliability of these systems. In response, this study introduces a cutting-edge computer vision-based methodology, the SEquential dashcam-based vEhicle localization frameworK Plus (SEEK+), designed to counteract GPS spoofing. By analyzing dashcam footage to ascertain a vehicle’s actual location, SEEK+ scrutinizes the authenticity of reported GPS data, effectively identifying spoofing incidents. The application of dashcam imagery for localization, however, presents inherent obstacles, such as adverse lighting and weather conditions, seasonal and temporal image variations, obstructions within the camera’s field of view, and fluctuating vehicle velocities. To overcome these issues, SEEK+ integrates innovative strategies within its framework, demonstrating superior efficacy over existing approaches with a notable detection accuracy rate of up to 94%.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"100 ","pages":"Article 101916"},"PeriodicalIF":3.0000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SEEK+: Securing vehicle GPS via a sequential dashcam-based vehicle localization framework\",\"authors\":\"Peng Jiang ,&nbsp;Hongyi Wu ,&nbsp;Yanxiao Zhao ,&nbsp;Dan Zhao ,&nbsp;Gang Zhou ,&nbsp;Chunsheng Xin\",\"doi\":\"10.1016/j.pmcj.2024.101916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Nowadays, the Global Positioning System (GPS) plays an critical role in providing navigational services for transportation and a variety of other location-dependent applications. However, the emergent threat of GPS spoofing attacks compromises the safety and reliability of these systems. In response, this study introduces a cutting-edge computer vision-based methodology, the SEquential dashcam-based vEhicle localization frameworK Plus (SEEK+), designed to counteract GPS spoofing. By analyzing dashcam footage to ascertain a vehicle’s actual location, SEEK+ scrutinizes the authenticity of reported GPS data, effectively identifying spoofing incidents. The application of dashcam imagery for localization, however, presents inherent obstacles, such as adverse lighting and weather conditions, seasonal and temporal image variations, obstructions within the camera’s field of view, and fluctuating vehicle velocities. To overcome these issues, SEEK+ integrates innovative strategies within its framework, demonstrating superior efficacy over existing approaches with a notable detection accuracy rate of up to 94%.</p></div>\",\"PeriodicalId\":49005,\"journal\":{\"name\":\"Pervasive and Mobile Computing\",\"volume\":\"100 \",\"pages\":\"Article 101916\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pervasive and Mobile Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1574119224000427\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pervasive and Mobile Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574119224000427","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

如今,全球定位系统(GPS)在为交通和其他各种依赖位置的应用提供导航服务方面发挥着至关重要的作用。然而,新出现的 GPS 欺骗攻击威胁损害了这些系统的安全性和可靠性。为此,本研究引入了一种基于计算机视觉的先进方法,即基于仪表盘的SEquential vEhicle localization frameworK Plus (SEEK+),旨在对抗GPS欺骗。通过分析仪表盘录像来确定车辆的实际位置,SEEK+ 可以仔细检查所报告的 GPS 数据的真实性,从而有效识别欺骗事件。然而,应用仪表盘摄像头图像进行定位存在固有的障碍,例如不利的照明和天气条件、季节和时间图像变化、摄像头视野内的障碍物以及波动的车辆速度。为了克服这些问题,SEEK+ 在其框架内集成了创新策略,与现有方法相比,显示出卓越的功效,检测准确率高达 94%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SEEK+: Securing vehicle GPS via a sequential dashcam-based vehicle localization framework

Nowadays, the Global Positioning System (GPS) plays an critical role in providing navigational services for transportation and a variety of other location-dependent applications. However, the emergent threat of GPS spoofing attacks compromises the safety and reliability of these systems. In response, this study introduces a cutting-edge computer vision-based methodology, the SEquential dashcam-based vEhicle localization frameworK Plus (SEEK+), designed to counteract GPS spoofing. By analyzing dashcam footage to ascertain a vehicle’s actual location, SEEK+ scrutinizes the authenticity of reported GPS data, effectively identifying spoofing incidents. The application of dashcam imagery for localization, however, presents inherent obstacles, such as adverse lighting and weather conditions, seasonal and temporal image variations, obstructions within the camera’s field of view, and fluctuating vehicle velocities. To overcome these issues, SEEK+ integrates innovative strategies within its framework, demonstrating superior efficacy over existing approaches with a notable detection accuracy rate of up to 94%.

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
Pervasive and Mobile Computing
Pervasive and Mobile Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
7.70
自引率
2.30%
发文量
80
审稿时长
68 days
期刊介绍: As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies. The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信