An evaluation of deep learning models for chargeback Fraud detection in online games

Author:

Wei Yu-ChihORCID,Lai You-Xin,Wu Mu-En

Funder

Ministry of Science and Technology, Taiwan

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Reference37 articles.

1. Wijman, T.: Newzoo’s games trends to watch in 2021, 19 (2019)

2. Intelligence, M.: Gaming industry–growth, trends, and forecast (2020–2025) (2020)

3. Lee, N., Yoon, H., Choi, D.: Detecting online game chargeback fraud based on transaction sequence modeling using recurrent neural network. In: International Workshop on Information Security Applications, pp. 297–309. Springer

4. Awoyemi, J.O., Adetunmbi, A.O., Oluwadare, S.A.: Credit card fraud detection using machine learning techniques: a comparative analysis. In: 2017 International Conference on Computing Networking and Informatics (ICCNI), pp. 1–9. IEEE

5. Seo, J.-H., Choi, D.: Feature selection for chargeback fraud detection based on machine learning algorithms. Int. J. Appl. Eng. Res. 11(22), 10960–10966 (2016)

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