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Hijacking an autonomous delivery drone equipped with the ACAS-Xu system

Abstract : In this paper, we want to show that automated anticollision systems in aeronautical industry such as ACAS-Xu are vulnerable to hijacking threats in a urban environment which is less controlled than conventional airspace. Using reinforcement learning methods, we demonstrate the possibility to hijack the mission of a delivery drone equipped with the ACAS-Xu system in a simulated environment. Our objectives are first, to illustrate the security (interception) vulnerabilities of autonomous system and secondly, to enrich reinforcement learning benchmarks with a new one that comes from an industrial aeronautical application.
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https://hal.archives-ouvertes.fr/hal-03693913
Contributor : Adrien Gauffriau Connect in order to contact the contributor
Submitted on : Monday, June 13, 2022 - 11:24:37 AM
Last modification on : Friday, July 1, 2022 - 3:52:08 AM

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ERTS2022_Hijacking_ACAS.pdf
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  • HAL Id : hal-03693913, version 1

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Adrien Gauffriau, David Bertoin, Jayant Sen Gupta. Hijacking an autonomous delivery drone equipped with the ACAS-Xu system. ERTS2022, Jun 2022, TOULOUSE, France. ⟨hal-03693913⟩

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