This paper is published in Volume-4, Issue-2, 2018
Area
Security
Author
Rushabh Jadvani, Vivek Parmar, Dhruvin Sangani, Payal Sanghavi
Org/Univ
Shah and Anchor Kutchhi Engineering College, Mumbai, Maharashtra, India
Pub. Date
23 April, 2018
Paper ID
V4I2-2098
Publisher
Keywords
Credit Card, Fraud detection, Hidden Markov model, Spike detection, Fuzzy C means, Communal detection

Citationsacebook

IEEE
Rushabh Jadvani, Vivek Parmar, Dhruvin Sangani, Payal Sanghavi. Hybrid methodology for credit card anomaly detection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Rushabh Jadvani, Vivek Parmar, Dhruvin Sangani, Payal Sanghavi (2018). Hybrid methodology for credit card anomaly detection. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.

MLA
Rushabh Jadvani, Vivek Parmar, Dhruvin Sangani, Payal Sanghavi. "Hybrid methodology for credit card anomaly detection." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.

Abstract

Nowadays, people prefer cashless transactions out of which card payment is most prominent. But with its popularity and ease of use, comes threat. The threat of fraud and misuse as we have seen in many debit card fraud cases wherein victims come to know about the fraud transactions done on their account only after the transaction was done and they couldn't do anything. Hence detecting such frauds while they are actually happening is difficult. It is only after the transaction is done, we get to know that this particular transaction was fraudulent. Hence in this paper, we have tried to throw some light on a combination approach that includes Hidden Markov Model and Fuzzy logic which we believe can help in accurate detection and prevention of frauds related to card payments.