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Secure Motion Verification using the Doppler Effect

Published: 18 July 2016 Publication History

Abstract

Future transportation systems highly rely on the integrity of spatial information provided by their means of transportation such as vehicles and planes. In critical applications (e.g. collision avoidance), tampering with this data can result in life-threatening situations. It is therefore essential for the safety of these systems to securely verify this information. While there is a considerable body of work on the secure verification of locations, movement of nodes has only received little attention in the literature. This paper proposes a new method to securely verify spatial movement of a mobile sender in all dimensions, i.e., position, speed, and direction. Our scheme uses Doppler shift measurements from different locations to verify a prover's motion. We provide formal proof for the security of the scheme and demonstrate its applicability to air traffic communications. Our results indicate that it is possible to reliably verify the motion of aircraft in currently operational systems with an equal error rate of zero.

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  • (2024)Secure Motion Verification for High Altitude Platforms with a Hybrid AOA-TDOA-FDOA SchemeWireless Artificial Intelligent Computing Systems and Applications10.1007/978-3-031-71470-2_12(139-150)Online publication date: 13-Nov-2024
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  • (2023)BTV2P: Blockchain-based Trust Model for Secure Vehicles and Pedestrians Networks2023 IEEE International Conference on Cyber Security and Resilience (CSR)10.1109/CSR57506.2023.10224934(148-153)Online publication date: 31-Jul-2023
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cover image ACM Conferences
WiSec '16: Proceedings of the 9th ACM Conference on Security & Privacy in Wireless and Mobile Networks
July 2016
242 pages
ISBN:9781450342704
DOI:10.1145/2939918
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Publication History

Published: 18 July 2016

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Author Tags

  1. aircraft
  2. avoidance
  3. collision
  4. doppler
  5. location verification
  6. motion
  7. physical
  8. safety
  9. security
  10. vehicular
  11. wireless

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WiSec '16 Paper Acceptance Rate 13 of 51 submissions, 25%;
Overall Acceptance Rate 98 of 338 submissions, 29%

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Cited By

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  • (2024)Secure Motion Verification for High Altitude Platforms with a Hybrid AOA-TDOA-FDOA SchemeWireless Artificial Intelligent Computing Systems and Applications10.1007/978-3-031-71470-2_12(139-150)Online publication date: 13-Nov-2024
  • (2024)VET: Autonomous Vehicular Credential Verification Using Trajectory and Motion VectorsSecurity and Privacy in Communication Networks10.1007/978-3-031-64954-7_8(140-164)Online publication date: 15-Oct-2024
  • (2023)BTV2P: Blockchain-based Trust Model for Secure Vehicles and Pedestrians Networks2023 IEEE International Conference on Cyber Security and Resilience (CSR)10.1109/CSR57506.2023.10224934(148-153)Online publication date: 31-Jul-2023
  • (2022)Cybersecurity Attacks on Software Logic and Error Handling Within ADS-B Implementations: Systematic Testing of Resilience and CountermeasuresIEEE Transactions on Aerospace and Electronic Systems10.1109/TAES.2021.313955958:4(2702-2719)Online publication date: Aug-2022
  • (2022)Analyzing Sequences of Airspace States to Detect Anomalous Traffic ConditionsIEEE Transactions on Aerospace and Electronic Systems10.1109/TAES.2021.312419958:3(1843-1857)Online publication date: Jun-2022
  • (2022)Self-Organizing Multilateration of an Unknown Number of TransmittersIEEE Open Journal of Vehicular Technology10.1109/OJVT.2022.31526993(85-97)Online publication date: 2022
  • (2021)Spoofing in civil aviation: Security and safety of GPS/GNSS and ADS-B systemsMegatrend revija10.5937/MegRev2103281K18:3(281-306)Online publication date: 2021
  • (2021)Intrusion Detection in Automatic Dependent Surveillance-Broadcast (ADS-B) with Machine Learning2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC)10.1109/DASC52595.2021.9594431(1-10)Online publication date: 3-Oct-2021
  • (2021)Studying Cybersecurity in Civil Aviation, Including Developing and Applying Aviation Cybersecurity Risk AssessmentIEEE Access10.1109/ACCESS.2021.31212309(143997-144016)Online publication date: 2021
  • (2020)MAVProProceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks10.1145/3395351.3399361(53-64)Online publication date: 8-Jul-2020
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