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Detecting collusive fraud in enterprise resource planning systems

Islam, Aminul, Corney, Malcolm W., Mohay, George M., Clark, Andrew J., Bracher, Shane, Raub, Tobias, & Flegel, Ulrich (2011) Detecting collusive fraud in enterprise resource planning systems. In Advances in Digital Forensics VII : 7th IFIP WG 11.9 International Conference on Digital Forensics Revised Selected Papers [IFIP Advances in Information and Communication Technology, 2011, Volume 361], Springer, Orlando, Florida, USA, pp. 143-153.

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Abstract

In today's technological age, fraud has become more complicated, and increasingly more difficult to detect, especially when it is collusive in nature. Different fraud surveys showed that the median loss from collusive fraud is much greater than fraud perpetrated by a single person. Despite its prevalence and potentially devastating effects, collusion is commonly overlooked as an organizational risk. Internal auditors often fail to proactively consider collusion in their fraud assessment and detection efforts. In this paper, we consider fraud scenarios with collusion. We present six potentially collusive fraudulent behaviors and show their detection process in an ERP system. We have enhanced our fraud detection framework to utilize aggregation of different sources of logs in order to detect communication and have further enhanced it to render it system-agnostic thus achieving portability and making it generally applicable to all ERP systems.

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ID Code: 40635
Item Type: Conference Paper
DOI: 10.1007/978-3-642-24212-0_11
ISBN: 978-3-642-24211-3
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300) > Computer System Security (080303)
Divisions: Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2011 (please consult the authors).
Deposited On: 11 Mar 2011 11:32
Last Modified: 29 Apr 2013 11:22

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