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Author: Admin | 2025-04-28
AbstractThe banking sector has recognized a radical transformation in its services, play an indispensable role in the development and feasibility of electronic commerce, which is coming to help the purchase to its customers. However, it becomes a major target for fraudsters through internet transactions that have become the cause of majority fraud. So, the fight against this fraud is an obligation on banks to ensure the safety of payment. We present our fraud detection approach based on data mining techniques: classification, clustering and research association. Similar content being viewed by others ReferencesFevad: Bilan e-commerce 2012 (2013). http://www.fevad.com/espacepresse/bilan-e-commerce-45-milliards-d-euros-en-2012OSCP: Rapport annuel. Observatoire de la sécurité des cartes de paiements (2011a). http://www.banque-france.fr/observatoire/telechar/2-statistiques-pour-fraude-2011-rapport-annuel-2011-observatoire-securite-cartes-paiement.pdfHassibi, K.: Detecting payment card fraud with neural networks. In: Lis-boa, P.J.G., Edisbury, B., Vellido, A. (eds.) Business Applications of Neural Networks: The State- of-the-Art of Real-World Applications. Progress in Neural Processing, vol. 13. Chap. 9, pp. 141–158. World Scientific Publishing (2000) Google Scholar Hand, D.J., Weston, D.J.: Statistical techniques for fraud detection, prevention and assessment in mining massive data sets for security. In: Fogelman-Soulié, F., Perrotta, D., Pikorski, J., Steinberger, R. (eds.) Advances in Data Mining, Search, Social Networks and Text Mining and Their Applications to Security. NATO ASI Series, pp. 257–270. IOS Press (2008). http://videolectures.net/mmdss07_hand_stf/Neural Network Rule Extraction to Detect Credit Card Fraud Google Scholar Cartes bancaires, le taux de fraude en progression écrit par Sara BAR-RHOUT, Catégorie: Économie. Publication: 24 mars 2015. Mis à jour: 1 avril 2015. Affichages: 328 Google Scholar Rapport annuel de l’observatoire de la sécurité des cartes de paiement, p. 16 (2014) Google Scholar Maes, S., Tuyls, K., Vanschoenwinkel, B., Manderick, B.: Credit card fraud detection using Bayesian and neural networks. In: Proceedings of NF 2002 (2002) Google Scholar Bachmayer, S.: Artificial Immune Systems, vol. 5132, pp. 119–131 (2008) Google Scholar Sánchez, D., Vila, M., Cerda, L., Serrano, J.: Association rules applied to credit card fraud detection. Exp. Syst. Appl. (2009). http://linkinghub.elsevier.com/retrieve/pii/S0957417408001176, http://www.springerlink.com/index/rq58w1v614933838pdfKrivko, M.: A hybrid model for plastic card fraud detection systems. Exp. Syst. Appl. (2010). http://linkinghub.elsevier.com/retrieve/pii/S0957417410001582Mahmoudi, N., Duman, E.: Detecting credit card fraud by modified fisher discriminant analysis. Exp. Syst. Appl. (2015). http://linkinghub.elsevier.com/retrieve/pii/S0957417414006617Van Vlasselaer, V., Bravo, C., Caelen, O., Eliassi-Rad, T., Akoglu, L., Snoeck, M., Baesens, B.: APATE: A Novel Approach for Automated Credit Card Transaction Fraud Detection using Network-Based Extensions. Decision Support Systems (2015). http://linkinghub.elsevier.com/retrieve/pii/S0167923615000846Kantardzic (2011) Google Scholar Mehboob, B., Liaqat, R.M. Abbas, N.: Student performance prediction and risk analysis by using data mining approach. J. Intell. Comput. 8(2) 49–57 (2017) Google Scholar Download references Author informationAuthors and AffiliationsLaboratory of Information Technology and Modeling, Faculty of Science ben M’sik, Hassan II University, Casablanca, MoroccoHafsa El-kaime, Mostafa Hanoune & Ahmed EddaouiAuthorsHafsa El-kaimeYou can also search for this author in PubMed Google ScholarMostafa HanouneYou can also search for this author in PubMed Google ScholarAhmed EddaouiYou can also search for this author in PubMed Google ScholarCorresponding authorCorrespondence to Hafsa El-kaime . Editor informationEditors and AffiliationsDepartment of Computer Science, Institute of Mathematics and Computer Science, Opole University, Opole, PolandJolanta Mizera-Pietraszko Digital Information Research Foundation , Chennai,
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