A role mining inspired approach to representing user behaviour in ERP systems
Contribuinte(s) |
Oyabu, Takashi Gen, Mitsuo |
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Data(s) |
14/12/2009
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Resumo |
Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach. |
Formato |
application/pdf |
Identificador | |
Publicador |
The Korean Institute of Industrial Engineers |
Relação |
http://eprints.qut.edu.au/29785/1/c29785.pdf http://www.apiems.net/conf2009/index.html Khan, Roheena Q., Corney, Malcolm W., Clark, Andrew J., & Mohay, George M. (2009) A role mining inspired approach to representing user behaviour in ERP systems. In Oyabu, Takashi & Gen, Mitsuo (Eds.) Proceedings of The 10th Asia Pacific Industrial Engineering and Management Systems Conference, The Korean Institute of Industrial Engineers, Kitakyushu International Conference Center, Kitakyushu, pp. 2541-2552. |
Direitos |
Copyright 2009 [please consult the authors] |
Fonte |
Faculty of Science and Technology; School of Information Technology; Information Security Institute |
Palavras-Chave | #080303 Computer System Security #Fraud Detection #Role Mining #Anomaly Detection #Enterprise Resource Planning |
Tipo |
Conference Paper |