# Cyber4 Drone: A Systematic Review of Cyber Security and Forensics in Next-Generation Drones
## 6 Drone Forensics
### Drone Forensic Datasets  
The information age has been ushered in by modern technology, which has made it simpler to create and store enormous data. Data generated and stored by a drone is vital during forensics. A dataset refers to a group of interconnected and distinct elements that possess varying interpretations depending on the situation, and it is employed for conducting experiments or analyses. The purpose of datasets is to assess or examine a particular process, such as evaluating a practitioner's performance in a training setting, assessing the capabilities of a tool or technique, or testing a hypothesis related to the functionality of the software or an application. A dataset may be used to analyze the situation and, more crucially, to aid in decision-making. A forensic dataset assists in the development and testing of forensic tools as well as investigator training prior to working on real-life scenarios. As a result, datasets and the applications that may be made with them are significant. In this section, we enlist various drone forensic datasets containing drone images acquired in different scenarios. The contents of these dataset ranges from logical, physical, and chip-off images. Moreover, some focus on RF signals acquired from different drone flights. Table 8 gives a comprehensive list of drone datasets available in the literature.  
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline  & **Tools** & **Description** & **OS** & **Os** & **Pr** & **Fw** & **Papers** \\ \hline \multirow{4}{*}{**CEReDS Drone Dataset**[149] & Google Maps & Flight path with timestamp & ALMWO & & ✓ & [145] \\  & Google Earth & Flight path with timestamp & ALMWO & & ✓ & [8,10,15,144,145] \\  & GPS Visualizer & Geo data visualization & O & & ✓ & [10,10] \\  & Dashware & Telemetry data representation & W & & ✓ & [144] \\  & ArcGIS PRO & 3D visualization & LMW & ✓ & [8] \\  & WebFlightPath & Flightbg parser & LMW & & ✓ & [10] \\ \hline \hline \end{tabular}
\end{table}
Table 7: _Cont._  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Dataset** & **Remarks** \\ \hline CFReDS Drone Dataset [149] & Includes 82 drone images from 30 drone models. Forensic images of data storage areas, controller, connected mobile device, and computer. \\ \hline Drone Detect [150] & Radio frequency dataset of DJI Mavic 2 Air S, DJI Mavic Pro, DJI Mavic Pro 2, DJI Inspire 2, DJI Mavic Mini, DJI Phantom 4, and the Parrot Disco. \\ \hline SARD [151] & Search and Rescue Image dataset was created with the goal of identifying casualties and people in search and recovery operations in UAV photos and videos. Contains 1981 hand-tagged images retrieved from video frames in the collection. \\ \hline Drone RF Signal [152] & Includes RF signals from several UAV remote controllers. There are 17 UAV radio controllers of eight multiple brands, each with 1000 RF signals lasting 0.25 milliseconds. \\ \hline UAVs for payload delivery [153] & Dataset of payload delivery in a smart UAV delivery system. \\ \hline Multi-Sensor Drone Detection [154] & UAVs included: a tiny version (Hubsan H107D+), a moderate drone (DJI Flame Wheel in quadcopter format), and a performance-grade model (DJI Flame Wheel in quadcopter configuration) (DJI Phantom 4 Pro). Includes 650 visible and infrared clips of UAVs, birds, aircraft, and choppers (365 IR and 285 visible). \\ \hline UAV attack dataset [155] & The collection includes recordings from a normal flight and one in which the UAV is subjected to GPS spoofing and jamming. \\ \hline DroneFace [156] & Face pictures acquired from a variety of angles and altitudes in an unrestricted atmosphere can be useful for future research into incorporating face detection and recognition methods into UAVs. \\ \hline \hline \end{tabular}
\end{table}
Table 8: Drone datasets available in the literature.