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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한산업공학회 Industrial Engineering & Management Systems Industrial Engineering & Management Systems 제9권 제2호
- 발행연도
- 2010.6
- 수록면
- 141 - 156 (16page)
이용수
초록· 키워드
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 predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.
#Fraud Detection
#Audit Trail Analysis
#Security
#Role Mining
#Anomaly Detection
#Enterprise Resource Planning Systems
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목차
- Abstract
- 1. INTRODUCTION
- 2. RELATED WORK
- 3. TRANSACTION PROFILES
- 4. EVALUATION
- 5. CONCLUSION AND FUTURE WORK
- ACKNOWLEDGMENT
- REFERENCES
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-ECN-0101-2013-530-003636468
