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Texas State University

Securing the ADS-B Protocol for Attack-resilient Multiple UAV Collision Avoidance

Abstract

dc:description.abstract

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 packets from surrounding UAVs. The proposed scheme enables UAVs or ground stations to identify dishonest UAVs and avoid collisions. The scheme was implemented and tested in the SITL (Software In The Loop) simulator to verify its ability to detect dishonest UAVs. The experiments showed that the scheme achieved the desired accuracy in both flight trajectory measurement and attack detection.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Computer Science
Grantor
Texas State University
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Languell, Zachary P.
Advisor dc:contributor.advisor
  • Gu, Qijun
Committee members dc:contributor.committeemember
  • Chen, Xiao
  • Guirguis, Mina

Subjects

dc:subject × 11

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10877/8000
OAI identifier oai:identifier
oai:digital.library.txst.edu:10877/8000

Chain of custody

source
Harvested from
Texas State University
Base URL
digital.library.txst.edu/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Languell, Zachary P.. Securing the ADS-B Protocol for Attack-resilient Multiple UAV Collision Avoidance. Masters thesis, Texas State University, 2019. https://hdl.handle.net/10877/8000