Various fields have benefited from machine learning (ML) applications (eg, health, finance,
military), mainly for automating tasks or improving decision making capability. The area of
digital forensics shows potential promise as categorizing content of seized devices for
potential evidentiary value is a complicated task due to the increasing amount of data that
needs to be processed. A rapid adaptation of ML-based products for such a real-life
application requires the creation of engineering knowledge that would make ML models …