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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Field Rob...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Field Robotics
Article . 2025 . Peer-reviewed
License: Wiley Online Library User Agreement
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DBLP
Article . 2026
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Cybersecurity Challenges and Solutions in Unmanned Aerial Vehicles (UAVs)

Authors: Roya Morshedi; S. Mojtaba Matinkhah;

Cybersecurity Challenges and Solutions in Unmanned Aerial Vehicles (UAVs)

Abstract

ABSTRACT Unmanned aerial vehicles (UAVs) have become indispensable assets across military, commercial, and civil domains due to their operational flexibility, cost‐efficiency, and real‐time sensing capabilities. However, the increasing integration of UAVs into critical infrastructure, combined with their reliance on wireless communications, Global Positioning System, and embedded control systems, has significantly expanded their cybersecurity attack surface. Despite growing research efforts, a comprehensive understanding of the unique security challenges facing UAV systems remains fragmented. This survey systematically analyzes the multifaceted cybersecurity threats targeting UAV platforms, encompassing communication links, navigation subsystems, onboard controllers, and ground control stations. We develop a unified threat taxonomy that classifies attacks such as spoofing, jamming, denial‐of‐service, hijacking, and malware injection, and assess their impacts on the core security pillars of confidentiality, integrity, and availability. Furthermore, existing defense mechanisms—including cryptographic protocols, intrusion detection systems, machine learning‐based anomaly detection, secure routing algorithms, and authentication schemes—are critically evaluated with respect to their effectiveness, scalability, resource consumption, and suitability for UAV‐specific operational constraints. Unlike previous surveys, this study synthesizes cross‐layer defense strategies and highlights open research gaps that remain underexplored. Finally, emerging directions such as blockchain integration, federated learning, and quantum‐resistant cryptographic frameworks are discussed, aiming to inspire robust and adaptive security architectures for next‐generation UAV ecosystems. This survey offers valuable insights for researchers, system architects, and policymakers committed to advancing UAV cybersecurity in increasingly contested and dynamic environments.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
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