TITLE:
A Comparative Study and Performance Analysis of ATM Card Fraud Detection Techniques
AUTHORS:
Md. Mijanur Rahman, Anuva Rani Saha
KEYWORDS:
ATM Card, Fraud Detection, Prevention Technology, Supervised and Unsupervised Technique
JOURNAL NAME:
Journal of Information Security,
Vol.10 No.3,
July
31,
2019
ABSTRACT: ATM
card fraud is increasing gradually with the expansion of modern technology and
global communication. In the whole world, it is
resulting in the loss of billions of dollars each year. Fraud detection systems have become
essential for all ATM card issuing banks to minimize their losses. The main
goals are, firstly, to review alternative techniques that have been used in
fraud detection and secondly compare and analyze these techniques that are
already used in ATM card fraud detection. Recently different card security
systems used different fraud detection techniques; these techniques are based
on neural network, genetic algorithm, hidden Markov model, Bayesian network,
decision tree, clustering method, support vector machine, etc. According to our
survey, the most important parameters used for comparing these fraud detection
systems are accuracy, speed and cost of fraud detection. This study is very
useful for any ATM card provider to choose an appropriate solution for fraud
detection problem and also enable us to build a hybrid approach for developing
some effective algorithms which can perform properly on fraud detection mechanism.