A System for Secure Remote Identification of Drones

Abstract

The rapid advancement of Unmanned Aerial Vehicles (UAVs), commonly known as drones, in sectors like logistics, surveillance, and national defense has necessitated robust regulatory and security measures. Recognizing this, the Federal Aviation Administration (FAA) has established standards for drone flight and operations. Central to these regulatory efforts is the Remote Identification (RID) concept, akin to a digital license plate for drones, which has proven to be an effective solution for addressing many drone-related challenges. This research successfully developed and implemented an RID system for UAVs, primarily targeting the prevention of malicious drones from masquerading their identities for illegal activities. In full compliance with FAA regulations and the ASTM F3411 standard, the main focus of this work was to secure communication between drones and observers using an advanced authentication mechanism. The completed design features a broadcast-based RID module, which ensures secure, low-power operation while meeting the real-time constraints specified by the ASTMF3411standard. This broadcast-based approach has been validated as a reliable solution across various operational environments, including regions with limited or no internet connectivity. A key achievement of this research was the successful integration of robust authentication within the broadcast framework. By implementing advanced cryptographic techniques, such as the Ed25519 digital signature scheme, the system effectively prevents identity spoofing and unauthorized drone usage. The real-time operation and lightweight implementation on FPGA hardware ensure compliance with FAA’s legal and safety standards while maintaining energy efficiency and performance. This research demonstrates significant advancements in UAV security and operational efficiency, addressing current challenges and aligning with the dynamic needs of modern drone technology and evolving regulatory requirements. This work marks a substantial contribution to UAV airspace safety, establishing a secure and practical RID solution for real-world applications.

Date of Award	17 Dec 2024
Original language	American English
Supervisor	Abdulhadi Shoufan (Supervisor)