Adaptive Position Prediction Based GNSS Spoofing Detection for Autonomous Vehicles

Jiesen Yang, Hong Liu, Hongxing Hu, Shouwei Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Automatic vehicles (AVs) have been a hot topic recently, but GNSS spoofing is becoming a technology that can be used manually and has a huge potential threat to AV security. This paper proposes a GNSS spoofing detection method based on vehicle position prediction and develops a prediction error model, which can dynamically adjust the detection threshold. The simulation results show that this adaptive detection threshold setting can keep the gap between the error distance and the detection threshold in a relatively stable range without spoofing, significantly reducing the possibility of false alarms. Besides, this position prediction method's horizontal error (around 0.01m) is minor enough to satisfy defense demands against spoofing attacks. Overall, the analyses reveal that the spoofing detection method is effective in spoofing attacks with offset in different directions.

Original languageEnglish
Title of host publicationProceedings - 2022 3rd International Conference on Electronics, Communications and Information Technology, CECIT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages428-434
Number of pages7
ISBN (Electronic)9798350331974
DOIs
StatePublished - 2022
Event3rd International Conference on Electronics, Communications and Information Technology, CECIT 2022 - Virtual, Online, China
Duration: 23 Dec 202225 Dec 2022

Publication series

NameProceedings - 2022 3rd International Conference on Electronics, Communications and Information Technology, CECIT 2022

Conference

Conference3rd International Conference on Electronics, Communications and Information Technology, CECIT 2022
Country/TerritoryChina
CityVirtual, Online
Period23/12/2225/12/22

Keywords

  • Autonomous Vehicles
  • GNSS Spoofing
  • Position Prediction

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