A Framework for Anomaly Pattern Recognition in Electronic Financial Transaction Using Moving Average Method
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.
KeywordsElectronic financial transaction Pattern recognition Moving average
This work is supported by the Korea Information Security Agency (H2101-12-1001).
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