Towards development of a high abstract model for drone forensic domain

• Main Authors: Alhussan, Amel Ali, Al-Dhaqm, Arafat Mohammed Rashad, Yafooz, Wael M. S., Abd. Razak, Shukor, Emara, Abdel Hamid M., Khafaga, Doaa Sami
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/103557/1/ArafatMohammedRashad2022_TowardsDevelopmentofaHighAbstractModel.pdf; http://eprints.utm.my/103557/; http://dx.doi.org/10.3390/electronics11081168
• Institution: Universiti Teknologi Malaysia

Drone Forensics (DRF) is one of the subdomains of digital forensics, which aims to capture and analyse the drone’s incidents. It is a diverse, unclear, and complex domain due to various drone field standards, operating systems, and infrastructure-based networks. Several DRF models and frameworks have been designed based on different investigation processes and activities and for the specific drones’ scenarios. These models make the domain more complex and unorganized among domain forensic practitioners. Therefore, there is a lack of a generic model for managing, sharing, and reusing the processes and activities of the DRF domain. This paper aims to develop A Drone Forensic Metamodel (DRFM) for the DRF domain using the metamodeling development process. The metamodeling development process is used for constructing and validating a metamodel and ensuring that the metamodel is complete and consistent. The developed DRFM consists of three main stages: (1) identification stage, (2) acquisition and preservation stage, and (3) examination and data analysis stage. It is used to structure and organize DRF domain knowledge, which facilitates managing, organizing, sharing, and reusing DRF domain knowledge among domain forensic practitioners. That aims to identify, recognize, extract and match different DRF processes, concepts, activities, and tasks from other DRF models in a developed DRFM. Thus, allowing domain practitioners to derive/instantiate solution models easily. The consistency and applicability of the developed DRFM were validated using metamodel transformation (vertical transformation). The results indicated that the developed DRFM is consistent and coherent and enables domain forensic practitioners to instantiate new solution models easily by selecting and combining concept elements (attribute and operations) based on their model requirement.