Ontology-Based Framework Applied to Money Laundering Investigations

Abstract

Criminal investigations face a deluge of structured and unstructured data obtained from heterogeneous sources like forensic reports or wiretap transcriptions. In these cases, finding relevant information can be a complex task. Ontologies have been successfully applied to several domains including legal, cyber crime and digital forensics. In this paper it is proposed a framework based on ontology engineering, that provides an unified approach to represent and reason with the criminal investigation data. Moreover, this framework is applied to the specific use case of money laundering.