Author:
Golait Snehal S.,Masidkar Ruthwick S.,Khobragade Kunal S.,Bhanarkar Prerna S.,Ganeshkar Purva,Ganeshkar Prishita
Publisher
Springer Nature Singapore
Reference25 articles.
1. Zhang, X., & Liu, Y. (2020). A deep learning-based credit card fraud detection system using autoencoders. Applied Sciences, 10(7), 2858. https://doi.org/10.3390/app10072858
2. Ahmed, M. T., & Alhossainy, A. A. (2020). Credit card fraud detection using machine learning algorithms. Journal of King Saud University - Computer and Information Sciences, 32(2), 210–219. https://doi.org/10.1016/j.jksuci.2019.01.009
3. Kim, H., & Lee, S. (2021). Anomaly detection-based credit card fraud detection system using one-class support vector machines. Expert Systems with Applications, 165, 113719.
4. Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys (CSUR), 41(3), 15.
5. Nilson Report. (2020). Global fraud losses on cards Reach $28.6 billion. [Online]. Available: https://nilsonreport.com/upload/content_promo/The_Nilson_Report_11-20_public.pdf