Abstract
We propose a fraud detection method based on the user accounts visualization and threshold-type detection. The visualization technique employed in our approach is the Self-Organizing Map (SOM). Since the SOM technique in its original form visualizes only the vectors, and the user accounts are represented in our work as the matrices storing a collection of records reflecting the user sequential activities, we propose a method of the matrices visualization on the SOM grid, which constitutes the main contribution of this paper. Furthermore, we propose a method of the detection threshold setting on the basis of the SOM U-matrix. The results of the conducted experimental study on real data in the field of telecommunications fraud detection confirm the advantages and effectiveness of the proposed approach.
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Olszewski, D., Kacprzyk, J., Zadrożny, S. (2013). Employing Self-Organizing Map for Fraud Detection. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_14
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DOI: https://doi.org/10.1007/978-3-642-38658-9_14
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