Digital evidence identification/classification study using causal relationship structure information

In this paper, we propose causal information necessary to effectively identify key clues and causes in order to analyze the causal relationship of the crime by extracting words and vocabulary corresponding to the criminal context from evidence files obtained for digital evidence analysis. This information is configured to recognize and classify individual names, extracts and categorizes crime-related persons, interpersonal relationships, criminal methods, and crime-related information, which will be used for crime prevention analysis and investigation using causal analysis techniques for future crimes.