CREDIT CARD FRAUD DETECTION USING DECISION TREE FOR TRACING EMAIL AND IP

Credit card fraud is a wide-ranging term for theft and fraud committed using a credit card or any similar payment mechanism as a fraudulent source of funds in a transaction. The purpose may be to obtain goods without paying, or to obtain unauthorized funds from an account. Transactions completed with credit cards seem to become more and more popular with the introduction of online shopping and banking. Correspondingly, the number of credit card frauds has also increased .Currently; data mining is a popular way to combat frauds because of its effectiveness. Data mining is a welldefined procedure that takes data as input and produces output in the forms of models or patterns. In other words, the task of data mining is to analyze a massive amount of data and to extract some usable information that we can interpret for future uses. Frauds has also increased .Currently, data mining is a popular way to combat frauds because of its effectiveness. Data mining is a well-defined procedure that takes data as input and produces output in the forms of models or patterns. In other words, the task of data mining is to analyze a massive amount of data and to extract some usable information that we can interpret for future uses.

[1]  Mads Haahr,et al.  A Case-Based Approach to Spam Filtering that Can Track Concept Drift , 2003 .

[2]  Ian Witten,et al.  Data Mining , 2000 .

[3]  Ben Kamens.  Bayesian Filtering : Beyond Binary Classification , 2005 .

[4]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[5]  Yishay Mansour,et al.  A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization , 1998, ICML.

[6]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[7]  Jon T. S. Quah,et al.  Real Time Credit Card Fraud Detection using Computational Intelligence , 2007, 2007 International Joint Conference on Neural Networks.

[8]  Salvatore J. Stolfo,et al.  Distributed data mining in credit card fraud detection , 1999, IEEE Intell. Syst..

[9]  G. V. Kass.  An Exploratory Technique for Investigating Large Quantities of Categorical Data , 1980 .

[10]  Yishay Mansour,et al.  On the boosting ability of top-down decision tree learning algorithms , 1996, STOC '96.

[11]  Stuart Maguire,et al.  Identifying risks during information system development: managing the process , 2002, Inf. Manag. Comput. Secur..

[12]  Shamik Sural,et al.  Credit card fraud detection: A fusion approach using Dempster-Shafer theory and Bayesian learning , 2009, Inf. Fusion.

[13]  Dr.R. Dhanapal,et al.  Customer Retention using Data Mining Techniques , 2010 .

[14]  อนิรุธ สืบสิงห์,et al.  Data Mining Practical Machine Learning Tools and Techniques , 2014 .

[15]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .