Semantic Forensic Investigation Framework for Drone Field

Abstract

The application of Unmanned Aerial Vehicles (UAVs) is extensive, with uses ranging from smart agriculture to photography, maintaining infrastructure, and disaster recovery. However, incidents involving unmanned aerial vehicles are increasing daily due to their widespread use in smart technologies. Therefore, this study focuses on the ground of drone forensic investigation to capture and investigate incidents involving unmanned aerial vehicles. To find drone incidents and identify the perpetrators, forensic drone investigation is used, such as determining when the drone incident occurred, what type of drone incident it was, and the exact moment the drone incident occurred. Several forensic models and frameworks for drones have been proposed to identify, capture and analyze various cybercrimes committed by drones. However, these works deal with drones from a technical standpoint; thus, a semantic forensic framework for unmanned aerial vehicles is required to facilitate the investigation process among domain investigators. Therefore, the objective of this study is to use the design science method to develop a semantic forensic investigation framework for drones. The designed framework includes three main abstract processes: (1) Preparation, (2) Gathering and preservation, and (3) Analysis and documentation. The qualitative technique was used to validate the designed framework (Comparison against other models). The designed framework is compared with other models to ensure that it is logical, complete, and useful in comparison to another drone forensic investigation domain models. The designed framework enables domain practitioners to easily create solution models based on their requirements. It proposed a modeling process that uses modeling rules to generate solution models.