Unmanned Aerial Vehicle Forensic Investigation Process: Dji Phantom 3 Drone As A Case Study

Drones (also known as Unmanned Aerial Vehicles, UAVs) is a potential source of evidence in a digital investigation, partly due to their increasing popularity in our society. However, existing UAV/drone forensics generally rely on conventional digital forensic investigation guidelines such as those of ACPO and NIST, which may not be entirely fit_for_purpose. In this paper, we identify the challenges associated with UAV/drone forensics. We then explore and evaluate existing forensic guidelines, in terms of their effectiveness for UAV/drone forensic investigations. Next, we present our set of guidelines for UAV/drone investigations. Finally, we demonstrate how the proposed guidelines can be used to guide a drone forensic investigation using the DJI Phantom 3 drone as a case study

Drone forensic analysis using open source tools

Carrying capabilities of drones and their easy accessibility to public have led to an increase in crimes committed using drones in recent years. For this reason, the need for forensic analysis of drones captured from the crime scenes and the devices used for these drones is also paramount. This paper presents the extraction and identification of important artefacts from the recorded flight data as well as the associated mobile devices using open source tools and some basic scripts developed to aid the analysis of two popular drone systems- the DJI Phantom 3 Professional and Parrot AR. Drone 2.0. Although different drones vary in their operations, this paper extends the extraction and analysis of the data from the drones and associated devices using some generic methods which are forensically sound adhering to the guidelines of the Association of Chief Police Officers (ACPO)

Drone Forensic Analysis Using Open Source Tools

Carrying capabilities of drones and their easy accessibility to public have led to an increase in crimes committed using drones in recent years. For this reason, the need for forensic analysis of drones captured from the crime scenes and the devices used for these drones is also paramount. This paper presents the extraction and identification of important artefacts from the recorded flight data as well as the associated mobile devices using open source tools and some basic scripts developed to aid the analysis of two popular drone systems- the DJI Phantom 3 Professional and Parrot AR. Drone 2.0. Although different drones vary in their operations, this paper extends the extraction and analysis of the data from the drones and associated devices using some generic methods which are forensically sound adhering to the guidelines of the Association of Chief Police Officers (ACPO)

A Digital Forensics Case Study of the DJI Mini 3 Pro and DJI RC

The consumer drone market is rapidly expanding with new drone models featuring unique variations of hardware and software. The rapid development of drone technology and variability in drone systems can make it difficult for digital forensic investigators and tools to keep pace and effectively extract and analyse digital evidence from drones. Furthermore, the growing popularity of drones and their increased use in illegal and harmful activities, such as smuggling, espionage, and even terrorism, has led to an increase in the number of drone forensic cases for authorities to manage. To assist forensic investigators, a static digital forensic case study was conducted on two drone devices recently released by Da-Jiang Innovations (DJI): the Mini 3 Pro drone, and its remote controller, the DJI RC. The study discovered the presence of several digital artefacts on both devices, including recorded media, flight logs, and other information that could help investigators trace the drone's usage and identify its operator. Additionally, this paper explored several methods for extracting and visualising the drone's flight history, and highlights some of the potential methods used to limit, obscure, or remove key types of digital evidence.Comment: 20 Pages, 23 figure

DROP (DRone Open source Parser) Your Drone: Forensic Analysis of the DJI Phantom III

The DJI Phantom III drone has already been used for malicious activities (to drop bombs, remote surveillance and plane watching) in 2016 and 2017. At the time of writing, DJI was the drone manufacturer with the largest market share. Our work presents the primary thorough forensic analysis of the DJI Phantom III drone, and the primary account for proprietary file structures stored by the examined drone. It also presents the forensically sound open source tool DRone Open source Parser (DROP) that parses proprietary DAT files extracted from the drone\u27s nonvolatile internal storage. These DAT files are encrypted and encoded. The work also shares preliminary findings on TXT files, which are also proprietary, encrypted, encoded, files found on the mobile device controlling the drone. These files provided a slew of data such as GPS locations, battery, flight time, etc. By extracting data from the controlling mobile device, and the drone, we were able to correlate data and link the user to a specific device based on extracted metadata. Furthermore, results showed that the best mechanism to forensically acquire data from the tested drone is to manually extract the SD card by disassembling the drone. Our findings illustrated that the drone should not be turned on as turning it on changes data on the drone by creating a new DAT file, but may also delete stored data if the drone\u27s internal storage is full

2023 SDSU Data Science Symposium Presentation Abstracts

This document contains abstracts for presentations and posters 2023 SDSU Data Science Symposium

2023 SDSU Data Science Symposium Presentation Abstracts

This document contains abstracts for presentations and posters 2023 SDSU Data Science Symposium

Forensic investigation of small-scale digital devices: a futuristic view

Small-scale digital devices like smartphones, smart toys, drones, gaming consoles, tablets, and other personal data assistants have now become ingrained constituents in our daily lives. These devices store massive amounts of data related to individual traits of users, their routine operations, medical histories, and financial information. At the same time, with continuously evolving technology, the diversity in operating systems, client storage localities, remote/cloud storages and backups, and encryption practices renders the forensic analysis task multi-faceted. This makes forensic investigators having to deal with an array of novel challenges. This study reviews the forensic frameworks and procedures used in investigating small-scale digital devices. While highlighting the challenges faced by digital forensics, we explore how cutting-edge technologies like Blockchain, Artificial Intelligence, Machine Learning, and Data Science may play a role in remedying concerns. The review aims to accumulate state-of-the-art and identify a futuristic approach for investigating SSDDs