Title: Drone forensics: examination and analysis

Authors: Farkhund Iqbal; Benjamin Yankson; Maryam A. AlYammahi; Naeema AlMansoori; Suaad Mohammed Qayed; Babar Shah; Thar Baker

Addresses: College of Technological Innovation, Zayed University, Abu Dhabi, UAE ' School of Applied Computing, Sheridan College, Oakville, Ontario, Canada; Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, Ontario, Canada ' College of Technological Innovation, Zayed University, Abu Dhabi, UAE ' College of Technological Innovation, Zayed University, Abu Dhabi, UAE ' College of Technological Innovation, Zayed University, Abu Dhabi, UAE ' College of Technological Innovation, Zayed University, Abu Dhabi, UAE ' Department of Computer Science, Liverpool John Moores University, UK

Abstract: Unmanned aerial vehicles (UAVs), also known as drones, provides unique functionalities, which allows area surveillance, inspection, surveying, unarmed cargo, armed attack machines, and aerial photography. Drones are susceptible to GPS spoofing attacks, integrity attacks and de-authentication attacks, which can allow criminals to access data, intercept the drone and use it commit a crime. Thus, this paper is presented to report on potential attacks against the Parrot Bebop 2 drone, and the ability for an investigator to collect evidence about the attacks on the drone. This paper aims at examining the possibility of establishing ownership and collecting data to reconstruct events, linking the drone controller with the drone to prove ownership, flight origins and other potentially useful information necessary to identify the proprietor of a crime. In addition, we have also proposed small-scale drone ontology for modelling drone context data, and simple forensic processing framework for small-scale drones.

Keywords: digital forensics; investigation; drone security; drone attack; context data; drone ontology.

DOI: 10.1504/IJESDF.2019.100473

International Journal of Electronic Security and Digital Forensics, 2019 Vol.11 No.3, pp.245 - 264

Received: 30 Jun 2017
Accepted: 15 Jan 2018
Published online: 29 Jun 2019 *

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