{"title":"All in one: Improving GPS accuracy and security via crowdsourcing","authors":"Mahsa Foruhandeh, Hanchao Yang, Xiang Cheng, Angelos Stavrou, Haining Wang, Yaling Yang","doi":"10.1016/j.comnet.2024.110775","DOIUrl":null,"url":null,"abstract":"<div><p>GPS is an integral part of billions of devices that serve a wide range of applications. This reliance upon GPS renders the users vulnerable to GPS spoofing attacks, especially when in need of precise or real-time location information. To protect commodity devices, we first propose a crowdsourcing-based method for detecting GPS spoofing. In this method, called method I, we leverage the orientation diversity of different users to expose spoofing attacks and, in many cases, the location of the attacker. In all scenarios, our method not only recovers the correct location but also significantly improves the location accuracy. This is an important incentive that can drive the adoption of our approach along with the use of privacy-preserving location sharing. Additionally, we leverage the users’ distances produced by GPS and Bluetooth measurements to detect discrepancies and account for errors, called Method II. Method II is robust even in the presence of multiple coordinate adversaries. The experimental results based on our prototype implementation and large-scale simulations demonstrate a detection rate as high as 98.72<!--> <!-->% and latency of 62<!--> <!-->ms with average localization error of 2.43<!--> <!-->m.</p></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389128624006078","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
GPS is an integral part of billions of devices that serve a wide range of applications. This reliance upon GPS renders the users vulnerable to GPS spoofing attacks, especially when in need of precise or real-time location information. To protect commodity devices, we first propose a crowdsourcing-based method for detecting GPS spoofing. In this method, called method I, we leverage the orientation diversity of different users to expose spoofing attacks and, in many cases, the location of the attacker. In all scenarios, our method not only recovers the correct location but also significantly improves the location accuracy. This is an important incentive that can drive the adoption of our approach along with the use of privacy-preserving location sharing. Additionally, we leverage the users’ distances produced by GPS and Bluetooth measurements to detect discrepancies and account for errors, called Method II. Method II is robust even in the presence of multiple coordinate adversaries. The experimental results based on our prototype implementation and large-scale simulations demonstrate a detection rate as high as 98.72 % and latency of 62 ms with average localization error of 2.43 m.
期刊介绍:
Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.