A Framework for Anomaly Pattern Recognition in Electronic Financial Transaction Using Moving Average Method

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)

Abstract

Nowadays, security incidents of financial IT services and internet banking hacking against the financial companies have occurred continuously, resulting in a loss of the financial IT systems. Accordingly, this paper based on ‘framework standards of financial transaction detection and response’ was designed to propose of anomaly Electronic Financial Transaction (EFT) pattern recognition and response for the method to detect anomaly prior behaviors and transaction patterns of users. It was applied to moving average based on the statistical basis.

Keywords

Electronic financial transaction Pattern recognition Moving average 

Notes

Acknowledgments

This work is supported by the Korea Information Security Agency (H2101-12-1001).

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Financial Security, Graduate School of Information SecurityKorea UniversitySeoulSouth Korea
  2. 2.Department of Information ManagementFar East UniversityChungbukSouth Korea
  3. 3.Graduate School of Information SecurityKorea UniversitySeoulSouth Korea

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