The week's pick
Reseach Article
A review of Fraud Detection Techniques: Credit Card
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 45 - Number 1 |
| Year of Publication: 2012 |
| Authors: Khyati Chaudhary, Jyoti Yadav, Bhawna Mallick |
10.5120/6748-8991
|
Khyati Chaudhary, Jyoti Yadav, Bhawna Mallick . A review of Fraud Detection Techniques: Credit Card. International Journal of Computer Applications. 45, 1 ( May 2012), 39-44. DOI=10.5120/6748-8991
Abstract
In present scenario when the term fraud comes into a discussion, credit card fraud clicks to mind so far. With the great increase in credit card transactions, credit card fraud has increasing excessively in recent years. Fraud detection includes monitoring of the spending behavior of users/ customers in order to determination, detection, or avoidance of undesirable behavior. As credit card becomes the most prevailing mode of payment for both online as well as regular purchase, fraud relate with it are also accelerating. Fraud detection is concerned with not only capturing the fraudulent events, but also capturing of such activities as quickly as possible. The use of credit cards is common in modern day society. Fraud is a millions dollar business and it is rising every year. Fraud presents significant cost to our economy worldwide. Modern techniques based on Data mining, Machine learning, Sequence Alignment, Fuzzy Logic, Genetic Programming, Artificial Intelligence etc. , has been introduced for detecting credit card fraudulent transactions. This paper shows how data mining techniques can be combined successfully to obtain a high fraud coverage combined with a low or high false alarm rate.
References
- Amlan Kundu, Suvasini Panigrahi, Shamik Sural and Arun K. Majumdar, "BLAST-SSAHA Hybridization for Credit Card Fraud Detection," IEEE Transactions On Dependable And Secure Computing, vol. 6, Issue no. 4, pp. 309-315, October-December 2009S.
- A. Shen, R. Tong, and Y. Deng, "Application of classification models on a. credit card fraud detection," June 2007.
- Dahl, J. : Card Fraud. In: Credit Union Magazine (2006).
- Ghosh and D. L. Reilly, "Credit Card Fraud Detection with a Neural-Network," Proc. 27th Hawaii International Conference on System Sciences: Information Systems: Decision Support and Knowledge-Based Systems, vol. 3, pp. 621-630, 1994.
- Kaiyong Deng, Ru Zhang, Hong Guo,Kaiyong Deng,R Zhang, Dongfang Zhang,WenFeng Jiang,Xinxin Niu "Analysis and Study on Detection of Credit Fraud in E-commerce 2011.
- Leila Seyedhossein, Mahmoud Reza Hashemi Mining Information from Credit Card Time Series for Timelier Fraud Detection International Symposium on Telecommunications 2010.
- Linda Delamaire (UK), Hussein Abdou (UK), John Pointon (UK), "Credit card fraud and detection techniques: a review"2009.
- M. F. Gadi, X. Wang, and A. P. Lago, "Comparison with parametric optimization in credit card fraud detection, 2008.
- Md Delwar Hussain Mahdi, Karim Mohammed Rezaul, Muhammad Azizur Rahman "Credit Fraud Detection in the Banking Sector in UK: A Focus on E-Business. " 2010.
- Mirjana Pejic-Bach, "Profiling intelligent systems applications in fraud detection and prevention: survey of research articles", 2010.
- Raghavendra Patidar, Lokesh Sharma, "Credit Card Fraud Detection Using Neural Network" 2011.
- S. Benson Edwin Raj, A. Annie Portia "Analysis on Credit Card Fraud Detection Methods" 2011.
- Sahin, Y. , Duman, E. : An overview of business domains where fraud can take place, and a survey of various fraud detection techniques. In: Proceedings of the 1st International Symposium on Computing in Science and Engineering, Aydin, Turkey (2010).
- Tej Paul Bhatla, Vikram Prabhu & Amit Dua "Understanding Credit Card Frauds," 2003.
- Y. Sahin, E. Duman "Detecting Credit Card Fraud by ANN and Logistic Regression" 2011.
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