QUT ePrints

A role mining inspired approach to representing user behaviour in ERP systems

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.

View at publisher

Abstract

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.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

353 since deposited on 21 Jan 2010
67 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 29785
Item Type: Conference Paper
Keywords: Fraud Detection, Role Mining, Anomaly Detection, Enterprise Resource Planning
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300) > Computer System Security (080303)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Information Technology
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2009 [please consult the authors]
Deposited On: 22 Jan 2010 09:35
Last Modified: 01 Mar 2012 00:04

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page