Abstract
We present an ontology-based and rules-based model of simple, but very typical, economic crimes, namely fraudulent disbursement in combination with money laundering. The extension of the previously proposed ontology model, called the “minimal model”, is used to capture the mechanism of the example cases. The conceptual minimal model consists of eight layers of concepts, structured in order to use available data on facts to uncover relations. In comparison to our previous work in which rules were restricted to criminal roles in only one company, where the crime originated, this work is able to capture roles and consequently criminal sanctions throughout the complete chain of conspiring companies. We are able to discover crime activity options (roles of particular type of owners, managers, directors and chairmen) using concepts, appropriate relations and rules. However, due to the varying size of incriminated companies the number of levels of responsibility ranges from one to three, that causes significant increase of necessary rules. These roles are phrased in the language of penal code sanctions. The roles of persons in the crime are mapped into a set of sanctions. We use the Semantic Data Library (SDL) with Jess engine as a reasoning tool to query and infer about crime scheme and sanctions. We present results achieved with our minimal model ontology. Prospects on future capabilities of our tools are presented.
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Bak, J., Jedrzejek, C., Falkowski, M. (2010). Application of an Ontology-Based and Rule-Based Model to Selected Economic Crimes: Fraudulent Disbursement and Money Laundering. In: Dean, M., Hall, J., Rotolo, A., Tabet, S. (eds) Semantic Web Rules. RuleML 2010. Lecture Notes in Computer Science, vol 6403. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16289-3_18
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DOI: https://doi.org/10.1007/978-3-642-16289-3_18
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