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Communication Dans Un Congrès Année : 2022

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

Résumé

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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Dates et versions

hal-03693913 , version 1 (13-06-2022)

Identifiants

  • HAL Id : hal-03693913 , version 1

Citer

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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