Watch the Skies: A Study on Drone Attack Vectors, Forensic Approaches, and Persisting Security Challenges

Amr Adel () and Tony Jan
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Amr Adel: Centre for Artificial Intelligence Research and Optimization (AIRO), Torrens University Australia, Ultimo, NSW 2007, Australia
Tony Jan: Centre for Artificial Intelligence Research and Optimization (AIRO), Torrens University Australia, Ultimo, NSW 2007, Australia

Future Internet, 2024, vol. 16, issue 7, 1-23

Abstract: In the rapidly evolving landscape of drone technology, securing unmanned aerial vehicles (UAVs) presents critical challenges and demands unique solutions. This paper offers a thorough examination of the security requirements, threat models, and solutions pertinent to UAVs, emphasizing the importance of cybersecurity and drone forensics. This research addresses the unique requirements of UAV security, outlines various threat models, and explores diverse solutions to ensure data integrity. Drone forensics, a field dedicated to the investigation of security incidents involving UAVs, has been extensively examined and demonstrates its relevance in identifying attack origins or establishing accident causes. This paper further surveys artifacts, tools, and benchmark datasets that are critical in the domain of drone forensics, providing a comprehensive view of current capabilities. Acknowledging the ongoing challenges in UAV security, particularly given the pace of technological advancement and complex operational environments, this study underscores the need for increased collaboration, updated security protocols, and comprehensive regulatory frameworks. Ultimately, this research contributes to a deeper understanding of UAV cybersecurity and aids in fostering future research into the secure and reliable operation of drones.

Keywords: unmanned aerial vehicles (UAVs); drone cybersecurity; threat models; drone forensics; security challenges; forensic methodologies (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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