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(Author / Reviewer / Editor)
Zachary P. Languell, Qijun Gu. A Multi-Point Distance-Bounding Protocol for Securing Automatic Dependent Surveillance-Broadcast in Unmanned Aerial Vehicle Applications[J]. Journal of Computer Science and Technology, 2020, 35(4): 825-842. DOI: 10.1007/s11390-020-0260-5
Citation: Zachary P. Languell, Qijun Gu. A Multi-Point Distance-Bounding Protocol for Securing Automatic Dependent Surveillance-Broadcast in Unmanned Aerial Vehicle Applications[J]. Journal of Computer Science and Technology, 2020, 35(4): 825-842. DOI: 10.1007/s11390-020-0260-5

A Multi-Point Distance-Bounding Protocol for Securing Automatic Dependent Surveillance-Broadcast in Unmanned Aerial Vehicle Applications

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  • Author Bio:

    Zachary P. Languell received his Bachelor's and Master's degrees in computer science from Texas State University, San Marcos, in 2016 and 2019 respectively. He is currently working as a software security engineer for Relativity, an e-discovery software solutions company, specializing in cloud and SaaS security.

  • Corresponding author:

    Qijun Gu E-mail: qijun@txstate.edu

  • Received Date: December 30, 2019
  • Revised Date: May 28, 2020
  • Published Date: July 19, 2020
  • The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol is being adopted for use in unmanned aerial vehicles (UAVs) as the primary source of information for emerging multi-UAV collision avoidance algorithms. The lack of security features in ADS-B leaves any processes dependent upon the information vulnerable to a variety of threats from compromised and dishonest UAVs. This could result in substantial losses or damage to properties. This research proposes a new distance-bounding scheme for verifying the distance and flight trajectory in the ADS-B broadcast data from surrounding UAVs. The proposed scheme enables UAVs or ground stations to identify fraudulent UAVs and avoid collisions. The scheme was implemented and tested in the ArduPilot SITL (Software In The Loop) simulator to verify its ability to detect fraudulent UAVs. The experiments showed that the scheme achieved the desired accuracy in both flight trajectory measurement and attack detection.
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