Impact Factor:6.549
Scopus Suggested Journal: |
International Journal
of Computer Engineering in Research Trends (IJCERT)
Scholarly, Peer-Reviewed, Open Access and Multidisciplinary
International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary
ISSN(Online):2349-7084 Submit Paper Check Paper Status Conference Proposal
[1] Dornadula, V. N., & Geetha, S. (2019). Credit Card Fraud Detection using Machine Learning Algorithms. Procedia Computer Science, 165, 631–641. doi:10.1016/j.procs.2020.01.057 [2] Venkata Suryanarayana, S., N. Balaji, G., & Venkateswara Rao, G. (2018). Machine Learning Approaches for Credit Card Fraud Detection. International Journal of Engineering & Technology, 7(2), 917. doi:10.14419/ijet.v7i2.9356 [3] Al-Shabi, M. (2019). Credit Card Fraud Detection Using Auto encoder Model in Unbalanced Datasets. Journal of Advances in Mathematics and Computer Science, 33(5), 1-16. https://doi.org/10.9734/jamcs/2019/v33i530192 [4] SADGALI, I., SAEL, N., & BENABBOU, F. (2019). Performance of machine learning techniques in the detection of financial frauds. Procedia Computer Science, 148, 45–54. doi:10.1016/j.procs.2019.01.007 [5] Leo, M., Sharma, S., & Maddulety, K. (2019). Machine Learning in Banking Risk Management: A Literature Review. Risks, 7(1), 29. doi:10.3390/risks7010029 [6] Sohony, I., Pratap, R., & Nambiar, U. (2018). Ensemble learning for credit card fraud detection. Proceedings of the ACM India Joint International Conference on Data Science and Management of Data - CoDS-COMAD ’18. doi:10.1145/3152494.3156815 [7] Carcillo, F., Le Borgne, Y.-A., Caelen, O., Kessaci, Y., Oblé, F., & Bontempi, G. (2019). Combining Unsupervised and Supervised Learning in Credit Card Fraud Detection. Information Sciences. doi:10.1016/j.ins.2019.05.042 [8] John O. Awoyemi Department of Computer Science Federal University of Technology Akure, Nigeria johntobaonline@yahoo.com [9] Choi, D., & Lee, K. (2018). An Artificial Intelligence Approach to Financial Fraud Detection under IoT Environment: A Survey and Implementation. Security and Communication Networks, 2018, 1–15. doi:10.1155/2018/5483472 [10] Popat, R. R., & Chaudhary, J. (2018). A Survey on Credit Card Fraud Detection Using Machine Learning. 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI). doi:10.1109/icoei.2018.8553963. [11] Roman Chuprina on April 14, 2020 at 1:30am; Blog, View. "The In-depth 2020 Guide to E-commerce Fraud Detection". www.datasciencecentral.com. Retrieved 2020-05-24. [12] Velasco, Rafael B.; Carpanese, Igor; Interian, Ruben; Paulo Neto, Octávio C. G.; Ribeiro, Celso C. (2020-05-28). "A decision support system for fraud detection in public procurement". International Transactions in Operational Research: itor.12811. doi:10.1111/itor.12811. ISSN 0969-6016. [13] Jump up to:a b c d Bolton, R. and Hand, D. (2002). Statistical fraud detection: A review. Statistical Science 17 (3), pp. 235-255 [14] Jump up to:a b G. K. Palshikar, The Hidden Truth – Frauds and Their Control: A Critical Application for Business Intelligence, Intelligent Enterprise, vol. 5, no. 9, 28 May 2002, pp. 46–51. [15] Vani, G. K. (February 2018). "How to detect data collection fraud using System properties approach". Multilogic in Science. VII (SPECIAL ISSUE ICAAASTSD-2018). ISSN 2277-7601. Retrieved February 2, 2019. [16] Michalski, R. S., I. Bratko, and M. Kubat (1998). Machine Learning and Data Mining – Methods and Applications. John Wiley & Sons Ltd. [17] Salazar, Addisson, et al. "Automatic credit card fraud detection based on non-linear signal processing." Security Technology (ICCST), 2012 IEEE International Carnahan Conference on. IEEE, 2012. [18] Delamaire, Linda, H. A. H. Abdou, and John Pointon. "Credit card fraud and detection techniques: a review." Banks and Bank system’s (2009). [19] Quinlan, J. Ross. "Induction of decision trees." Machine learning (1986). [20 Quinlan, J. R. (1987). "Simplifying decision trees". International Journal of Man-Machine Studies.
![]() | V7I901.pdf |
Latest issue :Volume 10 Issue 1 Articles In press
☞ INVITING SUBMISSIONS FOR THE NEXT ISSUE : |
---|
☞ LAST DATE OF SUBMISSION : 31st March 2023 |
---|
☞ SUBMISSION TO FIRST DECISION : In 7 Days |
---|
☞ FINAL DECISION : IN 3 WEEKS FROM THE DAY OF SUBMISSION |
---|