원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.6 No.4
2012.10
pp.69-78
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper discussed the past works on fraud detection system and highlights their deficiencies. A probabilistic based model was proposed to serve as a basis for mathematical derivation for adaptive threshold algorithm for detecting anomaly transactions. The model was optimized with Baum-Welsh and hybrid posterior-Viterbi algorithms. A credit card transactional data was simulated, trained and predicted for fraud. And finally, the proposed model was evaluated with different metric. The results showed that with the optimization of parameters, posterior-Viterbi cum new detection model performed better than Viterbi cum old detection model.
목차
Abstract
1. Introduction
1.1. Hidden Markov Model
1.2. Posterior-Viterbi Decoding
1.3. Performance Metrics
2. Architecture of the CCFDS
2.1 Cardholder’s Transactions Details
2.2 Data Preparation
2.3 Prediction Phase
2.4 Detection Stage
3. Experimental Setup
4. Discussion of Results
5. Conclusion
References
Appendix A
1. Introduction
1.1. Hidden Markov Model
1.2. Posterior-Viterbi Decoding
1.3. Performance Metrics
2. Architecture of the CCFDS
2.1 Cardholder’s Transactions Details
2.2 Data Preparation
2.3 Prediction Phase
2.4 Detection Stage
3. Experimental Setup
4. Discussion of Results
5. Conclusion
References
Appendix A
저자정보
참고문헌
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