Cyber threat in drone systems: bridging real-time security, legal admissibility, and digital forensic solution readiness
The rapid expansion of drones otherwise known as Unmanned Aerial Vehicles (UAVs), in critical sectors has increased their exposure to cyber threats such as GPS spoofing, command hijacking, and firmware tampering. Existing forensic tools often fail to address UAV-specific challenges like volatile memory and limited storage, hindering effective investigations. Hence, to address this gap, this study proposes the Enhanced UAV Forensic Framework (EUAVFF) a modular, forensic-by-design model integrating blockchain audit trails, secure logging, telemetry offloading, and UAV-friendly encryption. Validated through a literature review and a stakeholder survey (n = 100), results showed that over 70% of respondents lacked awareness of UAV cyber risks, and current drones were rated poorly in key forensic areas, including tamper-proof logging and legal evidence handling. Only 28% were familiar with drone-specific threats, reflecting critical gaps in preparedness.These findings emphasize the urgent need for proactive forensic integration. EUAVFF offers a structured path to secure, accountable, and resilient UAV operations in increasingly hostile cyber environments.
Authors
- Onur Osman (ORCID: https://orcid.org/0000-0001-7675-7999)
- Abiodun Esther Omolara (ORCID: https://orcid.org/0000-0002-7801-2541)
- Oludare Isaac Abiodun (ORCID: https://orcid.org/0000-0003-0138-6446)
- Usman Mohammed
- Jawad Rasheed (ORCID: https://orcid.org/0000-0003-3761-1641)
- Patricia Manko Lar
- Philip Oyadiran Adeyinka
- Adeola Grace Olugbenga
Institutions
- İstanbul Sabahattin Zaim Üniversitesi (TR)
- Applied Science Private University (JO)
- University of Jos (NG)
- İstanbul Nişantaşı Üniversitesi (TR)
- Istanbul Medipol University (TR)
- University of Abuja Teaching Hospital (NG)
- Istanbul University (TR)
- University of Abuja (NG)
Publication Details
- Journal
- Frontiers in Communications and Networks
- Published
- 2025-09-24
- DOI
- https://doi.org/10.3389/frcmn.2025.1661928
- Citations
- 4
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 19.97
Funders
- Tertiary Education Trust Fund