Digital Forensic Analysis of UAV Flight Data Using Static and Dynamic Methods in Coal Mining Area
Abstract
Unmanned Aerial Vehicles (UAV) have become vital tools in industrial sectors such as coal mining for site inspections and operational monitoring. However, unauthorized UAV flights present security risks that necessitate forensic investigation. This study examines a forensic case involving a DJI Mini 3 UAV suspected of crossing company boundaries. Using the Conceptual Digital Forensics Model for the Drone Forensic Field, both static and dynamic forensic acquisition methods were applied. Static acquisition recovered 53 photographs, 11 videos, 11 audio files, 10 deleted photos, 4 deleted videos, and 3 unidentified log files. Dynamic acquisition yielded 64 media files including 63 photographs (.JPG and .jpg) with 10 deleted, 14 videos (.MP4, .MOV, .SWF) with 6 deleted, 11 audio files, 4 plain text files, 31 deleted files, 3 EXIF metadata records containing GPS coordinates, and 3 unidentified log files. The GPS data from EXIF metadata was visualized in Google Earth to map flight paths and confirm boundary violations. These findings demonstrate that dynamic acquisition retrieves a more comprehensive artifact set than static acquisition. This study highlights the importance of UAV digital forensics in supporting security investigations and ensuring compliance with industrial UAV policies.
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