Credit Card Fraud Detection Techniques Under IoT Environment: A Survey

Author:

Kanchana M.,Naresh R.,Deepa N.,Pandiaraja P.,Stephan Thompson

Publisher

Springer International Publishing

Reference38 articles.

1. Makki, S., & Assaghir, Z. (2019). An experimental study with imbalanced classification approaches for credit card fraud detection. IEEE Access, 7, 93010–93022.

2. Dubey, S., Jain, Y., Jain, S., & Tiwari, N. (2019). A comparative analysis of various credit card fraud detection techniques. International Journal of Recent Technology and Engineering, 7, 402–407.

3. Tharakunnel, K., Jha, S., Siddhartha, B., & Westland, J. C. (2011). Data mining for credit card fraud: A comparative study. Decision Support Systems, 50, 602–613. Elsevier.

4. Rao, B., Freisleben, B., & Aleskerov, E. (1998). A neural network-based database mining system for credit card fraud detection. In Proceedings of the computational intelligence for financial engineering (IAFE). IEEE.

5. Majumdar, A., Kundu, A., Srivastava, A., & Sural, S. (2008). Credit card fraud detection using hidden Markov model. IEEE Transactions on Dependable and Secure Computing, 5, 37–48.

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