Specification and implementation of a data generator to simulate fraudulent user behavior

Galina Baader, Robert Meyer, Christoph Wagner, Helmut Krcmar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Fraud is a widespread international problem for enterprises. Organizations increasingly use self-learning classifiers to detect fraud. Such classifiers need training data to successfully distinguish normal from fraudulent behavior. However, data containing authentic fraud scenarios is often not available for researchers. Therefore, we have implemented a data generation tool, which simulates fraudulent and non-fraudulent user behavior within the purchase-to-pay business process of an ERP system. We identified fraud scenarios from literature and implemented them as automated routines using SAP’s programming language ABAP. The data generated can be used to train fraud detection classifiers as well as to benchmark existing ones.

Original languageEnglish
Title of host publicationBusiness Information Systems - 19th International Conference, BIS 2016, Proceedings
EditorsBogdan Franczyk, Witold Abramowicz, Rainer Alt
PublisherSpringer Verlag
Pages67-78
Number of pages12
ISBN (Print)9783319394251
DOIs
StatePublished - 2016
Event19th International Conference on Business Information Systems, BIS 2016 - Leipzig, Germany
Duration: 6 Jul 20168 Jul 2016

Publication series

NameLecture Notes in Business Information Processing
Volume255
ISSN (Print)1865-1348

Conference

Conference19th International Conference on Business Information Systems, BIS 2016
Country/TerritoryGermany
CityLeipzig
Period6/07/168/07/16

Keywords

  • ABAP
  • BAPI
  • BDC
  • Data generation
  • Fraud scenarios
  • Purchase-to-pay process
  • SAP ERP
  • User simulation

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