In this paper, we present new methods for learning the individual patterns of a card user's transaction amount and the region in which he or she uses the card, for a given period, and for determining whether the specified transaction is allowable in accordance with these learned user transaction patterns. Then, we classify legitimate transactions and fraudulent transactions by setting thresholds based on the learned individual patterns.
Bibliographical notePublisher Copyright:
Copyright © 2015 The Institute of Electronics, Information and Communication Engineers.
- Association rule
- Fraud detection
- Gaussian processes
- Pattern mining
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence