Monte-Carlo Filesystem Search – A crawl strategy for digital forensics

Criminal investigations invariably involve the triage or cursory examination of relevant electronic media for evidentiary value. Legislative restrictions and operational considerations can result in investigators having minimal time and resources to establish such relevance, particularly in situations where a person is in custody and awaiting interview. Traditional uninformed search methods can be slow, and informed search techniques are very sensitive to the search heuristic's quality. This research introduces Monte-Carlo Filesystem Search, an efficient crawl strategy designed to assist investigators by identifying known materials of interest in minimum time, particularly in bandwidth constrained environments. This is achieved by leveraging random selection with non-binary scoring to ensure robustness. The algorithm is then expanded with the integration of domain knowledge. A rigorous and extensive training and testing regime conducted using electronic media seized during investigations into online child exploitation proves the efficacy of this approach.