Forensic Black Box Architecture for Digital Evidence Analysis

Abstract

Digital forensics faces challenges of consistently interpreting complex data. Therefore, tech-nically possible alternative meanings need to be considered alongside the main research hypotheses when analysing digital traces. This becomes especially critical in cases involving missing or synthetic data, where the distinction between evidence-based conclusions and theoretical possibilities guarantees the integrity of forensic findings. To practically address the problem, the author proposes an architectural model of a “forensic black box” designed for forensic interpretations. This concept is consistent with Jeong Jong Chan’s forensic black box for data validation, which integrates GPS, inertial navigation, OBD2, and visual data to detect and document events in a vehicle-based example, such as collisions. Consistent interpretation of sensor data in such systems relies heavily on the adequacy condition, which requires that two identical data instances do not produce different classifications. Applying this condition in forensic systems enhances logical consistency, supports reliable reconstruc-tion of the incident, and supports the evidentiary value of digital findings in a legal context.