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.     

Space–Time Patterns of Risk: A Cross National Assessment of Residential Burglary Victimization

Using epidemiological techniques for testing disease contagion, it has recently been found that in the wake of a residential burglary, the risk to nearby homes is temporarily elevated. This paper demonstrates the ubiquity of this phenomenon by analyzing space–time patterns of burglary in 10 areas, located in five different countries. While the precise patterns vary, for all areas, houses within 200 m of a burgled home were at an elevated risk of burglary for a period of at least two weeks. For three of the five countries, differences in these patterns may partly be explained by simple differences in target density. The findings inform theories of crime concentration and offender targeting strategies, and have implications for crime forecasting and crime reduction more generally.