A Study on Drone Hacking: Vulnerabilities and Mitigation Techniques

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Open Access

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Notice

nThis is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.n

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Year : 2025 [if 2224 equals=””]23/09/2025 at 10:09 AM[/if 2224] | [if 1553 equals=””] Volume : 01 [else] Volume : 01[/if 1553] | [if 424 equals=”Regular Issue”]Issue : [/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02 | Page : 1 8

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    By

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    Syed Salman Naqvi,

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  1. Independent Researcher, Cyber Security Specialist, Hobart, TAS 7000, Launceston, Tasmania, Tasmania, Australia

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Abstract

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nThis paper explores the current cybersecurity landscape surrounding Unmanned Aerial Systems (UAS), commonly known as drones. With rapid growth in commercial and recreational drone use, the risk of cyber-attacks has also increased. This study highlights real-world vulnerabilities such as GPS spoofing, Wi-Fi hijacking, and firmware exploitation. It also suggests practical mitigation techniques, including encryption, real-time anomaly detection using machine learning, and secure communication protocols. The goal is to support researchers, developers, and regulators in creating more secure drone systems.

 

What are the main findings?

The research provides actionable guidance for engineers and regulators in securing drone operations.

Findings support the development of robust cybersecurity frameworks for drone integration in civilian and defense sectors.

 

What is the implication of the main finding?

The identification of real-world vulnerabilities like GPS spoofing, Wi-Fi hijacking, and firmware exploits underscores that drone manufacturers and integrators must bake robust security measures—such as encrypted communications, authenticated GPS modules, and digitally signed firmware—into every stage of system design rather than treating security as an afterthought.

To keep pace with evolving cyber threats, operators and regulators alike will need to adopt and enforce standards around practices such as real-time anomaly detection (leveraging lightweight ML models onboard), rotating encryption keys, and frequency-hopping RF protocols, ensuring that both commercial and recreational drone deployments maintain a baseline of resilience against sophisticated attacks.nn

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Keywords: Unmanned aerial systems: drone cyber security: GPS spoofing: Wifi hijacking

n[if 424 equals=”Regular Issue”][This article belongs to International Journal on Drones ]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in International Journal on Drones (ijd)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article:
nSyed Salman Naqvi. [if 2584 equals=”][226 wpautop=0 striphtml=1][else]A Study on Drone Hacking: Vulnerabilities and Mitigation Techniques[/if 2584]. International Journal on Drones. 18/09/2025; 01(02):1-8.

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How to cite this URL:
nSyed Salman Naqvi. [if 2584 equals=”][226 striphtml=1][else]A Study on Drone Hacking: Vulnerabilities and Mitigation Techniques[/if 2584]. International Journal on Drones. 18/09/2025; 01(02):1-8. Available from: https://journals.stmjournals.com/ijd/article=18/09/2025/view=0

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  1. Humphreys, T.E. Protecting UAVs from GPS Spoofing. IEEE Secur. Priv. 2023, Volume, page range.
  2. Pidikiti, S.; et al. Drone Wi-Fi Security Analysis. Wirel. Netw. 2024, Volume, page range.
  3. Trend Micro. Firmware Bugs in DJI Systems. Res. Rep. 2024, Volume, page range.
  4. Sharma, R. Command Injection Attacks on UAV Protocols. CyberTech J. 2025, Volume, page range.
  5. Khan, A.; et al. Bluetooth and RF Vulnerabilities in Drones. Infosec Today 2023, Volume, page range.
  6. Garg, S.; et al. ML-Based Intrusion Detection for IoT Systems. Cybersecur. 2024, Volume, page range.
  7. Raza, A.; Hardy, L.; Roehrer, E.; Yeom, S.; Kang, B.H. GPSPiChain: Blockchain and AI-Based Self-Contained Anomaly Detection Family Security System in Smart Home. Journal of Systems Science and Systems Engineering, 2021, 30, 433–449.
  8. Hameed, K.; Raza, A.; Garg, S.; Amin, M.B. A Blockchain-Based Decentralised and Dynamic Authorisation Scheme for the Internet of Things. SSRN, 2023.
  9. Omolara, A.E.; Alawida, M.; Abiodun, O.I. Drone Cybersecurity Issues, Solutions, Trend Insights and Future Perspectives: A Survey. Neural Computing and Applications, 2023, 35, 23063–23101.
  10. Pyzynski, M.; Balcerzak, T. Cybersecurity of the Unmanned Aircraft System (UAS). Journal of Intelligent & Robotic Systems, 2021, 102, 35

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Original Research

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Volume 01
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02
Received 24/07/2025
Accepted 08/09/2025
Published 18/09/2025
Retracted
Publication Time 56 Days

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