Title :
A new user-based model for credit card fraud detection based on artificial immune system
Author :
Soltani, Neda ; Akbari, Mohammad Kazem ; Javan, Mortaza Sargolzaei
Author_Institution :
Fac. of Comput. Eng. & Inf. Technol., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
In this paper we present a new model based on Artificial Immune System for credit card fraud detection. In this model, which is based on Artificial Immune Recognition System, user behavior is considered. The model puts together the two methodologies of fraud detection, namely tracking account behavior and general thresholding. The system generates normal memory cells using each user´s transaction records, yet fraud memory cells are generated based on all fraudulent records. To get more accurate results, we have performed analysis on training data in order to control the number of memory cells. During the test phase each user´s transaction is presented to his/her own normal memory cells, together with fraud memory cells.
Keywords :
artificial immune systems; credit transactions; data analysis; fraud; account behavior tracking; artificial immune recognition system; credit card fraud detection; fraud memory cells; fraudulent records; general thresholding; normal memory cell generation; training data analysis; user behavior; user transaction records; user-based model; Algorithm design and analysis; Classification algorithms; Computers; Credit cards; Detectors; Immune system; Training; Artifical Immune System; Credit card Fraud Detection; User profiling;
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
Conference_Location :
Shiraz, Fars
Print_ISBN :
978-1-4673-1478-7
DOI :
10.1109/AISP.2012.6313712