An ontology for promoting controlled experimentation in digital forensics

Abstract

Experimentation is a crucial method in empirical inquiry and is widely applied in Computer Science. Controlled experimentation ensures reproducibility, transparency, and reliability of findings, making the process more formal. Digital forensics (DF) lacks formalization of controlled experimental processes, leading to inadequate and informal research, making findings less transparent, reproducible, and reliable. Furthermore, existing works in this area often lack detailed descriptions of the controlled experimental decision-making procedures. To address these issues, we developed an ontology to formalize the concepts and terms used in DF-controlled experiments. The ontology was constructed based on an existing conceptual model for DF-controlled experiments. The ontology's conceptual model is represented by UML class diagrams, and the OWL language was employed to code it. Moreover, the ontology underwent evaluation by researchers and experts in DF experimentation, with the results indicating the capability of the ontology to formalize DF experimental concepts. The contribution of this ontology is to assist DF researchers and practitioners in properly documenting their controlled experiments. This will enhance the formality of the experimental process and promote the findings' reproducibility, transparency, and reliability. For researchers, the ontology's main contribution lies in influencing how these experiments are conducted, potentially impacting their transfer to industry. Practitioners stand to benefit by adopting formal experimental procedures for testing, assessing, and acquiring DF-related technology.