期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2010
卷号：10
期号：8
页码：123-130
出版社：International Journal of Computer Science and Network Security
摘要：The detection of fraudulent transactions in credit card world is an important application of classification techniques. As human behavior is unpredictable classifying any transaction either as fraud or non-fraud is not acceptable. In all of the previous studies, the transactions were classified in only two levels either fraud or legitimate. An approach where the credit card transactions can be classified in various fraud levels depending on different fraudulent situations mined from the historical behavior of the customers is proposed and implemented. To perform the classification, Efficient Scalable Multilevel Classifier (ESMC) algorithm is developed. Our algorithm is scalable to large dataset and results shows better accuracy than the previous algorithm implemented for credit card fraud detection. The concept of multi-dimensional decision tree is introduced to have better scalability in the field of distributed databases.
关键词：Distributed data Mining; Decision Tree; Pruning; Intrusion Detection
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