%0 Conference Paper %1 quteprints32405 %A Islam, Asadul Khandoker %A Corney, Malcolm W. %A Mohay, George M. %A Clark, Andrew J. %A Bracher, Shane %A Tobias, Raub %A Flegel, Ulrich %B International Information Security Conference (SEC 2010) : Security and Privacy : Silver Linings in the Cloud %C Brisbane Convention & Exhibition Centre, Brisbane, Queensland %D 2010 %I Springer %K ERP forensic_analysis synthetic_data %P 112--123 %T Fraud detection in ERP systems using scenario matching %U http://eprints.qut.edu.au/32405/ %X ERP systems generally implement controls to prevent certain common kinds of fraud. In addition however, there is an imperative need for detection of more sophisticated patterns of fraudulent activity as evidenced by the legal requirement for company audits and the common incidence of fraud. This paper describes the design and implementation of a framework for detecting patterns of fraudulent activity in ERP systems. We include the description of six fraud scenarios and the process of specifying and detecting the occurrence of those scenarios in ERP user log data using the prototype software which we have developed. The test results for detecting these scenarios in log data have been verified and confirm the success of our approach which can be generalized to ERP systems in general.

@inproceedings{quteprints32405, abstract = {ERP systems generally implement controls to prevent certain common kinds of fraud. In addition however, there is an imperative need for detection of more sophisticated patterns of fraudulent activity as evidenced by the legal requirement for company audits and the common incidence of fraud. This paper describes the design and implementation of a framework for detecting patterns of fraudulent activity in ERP systems. We include the description of six fraud scenarios and the process of specifying and detecting the occurrence of those scenarios in ERP user log data using the prototype software which we have developed. The test results for detecting these scenarios in log data have been verified and confirm the success of our approach which can be generalized to ERP systems in general.}, added-at = {2020-07-27T12:08:27.000+0200}, address = {Brisbane Convention \& Exhibition Centre, Brisbane, Queensland}, author = {Islam, Asadul Khandoker and Corney, Malcolm W. and Mohay, George M. and Clark, Andrew J. and Bracher, Shane and Tobias, Raub and Flegel, Ulrich}, biburl = {https://www.bibsonomy.org/bibtex/22f3f67d09392b293e594637a1ffe9527/tritsch}, booktitle = {International Information Security Conference (SEC 2010) : Security and Privacy : Silver Linings in the Cloud}, interhash = {f3177e8ddfdf707a737d170efe103061}, intrahash = {2f3f67d09392b293e594637a1ffe9527}, keywords = {ERP forensic_analysis synthetic_data}, month = {September}, note = {Accepted papers will be presented at the conference and published in the IFIP AICT (Advances in Information and Communication Technology) Series by Springer.}, pages = {112--123}, publisher = {Springer}, timestamp = {2020-07-27T12:46:57.000+0200}, title = {Fraud detection in ERP systems using scenario matching}, url = {http://eprints.qut.edu.au/32405/}, year = 2010 }