AI-driven dataset creation in mobile forensics using LLM-based storyboards

The generation of datasets is essential for training and validation tasks in digital forensics. Currently, the processes of data generation and provisioning are mainly performed manually. In the field of mobile forensics, there are only a limited number of tools available that aid in populating and injecting data into mobile devices. In this paper, we introduce a novel method for automatic data generation using an AI-driven approach. We present a comprehensive toolchain for dataset creation, focusing on developing a dynamic model (storyboard) with the assistance of large language model (LLM) agents. The generated sequences of activities are then automatically executed on mobile devices. Our proposed approach has been successfully implemented within the data creation and injection framework called AutoPodMobile (APM) as part of a proof-of-concept study. For data generated through AI methods, a validation is presented as well. The paper ends with a brief discussion of the results and the next steps planned. • Method creates synthetic datasets for mobile forensics. • AI-driven model creation using LLM-agents. • Integrated toolchain, covering all steps of the model creation process. • Proof-of-concept study.