Open Access Open Access  Restricted Access Subscription Access

A Machine Learning Framework for Adaptive FinTech Security Provisioning

Hyun Jung La,
Soo Dong Kim,

Abstract


FinTech services bring an elevated level of security concerns due to the non-conventional characteristics such as diverse and evolving transaction models. Hence, conventional financial security provisioning approaches have limited applicability, rather, it requires more effective, intelligent, and reactive anomaly management for FinTech transactions. We present a comprehensive framework for managing FinTech transactions which utilizes machine learning-based intelligence in deriving anomaly detection models and adaptive FinTech security provision. And, we define a formal model of the anomaly management, and present a software framework implementing the model.


Citation Format:
Hyun Jung La, Soo Dong Kim, "A Machine Learning Framework for Adaptive FinTech Security Provisioning," Journal of Internet Technology, vol. 19, no. 5 , pp. 1545-1553, Sep. 2018.

Full Text:

PDF

Refbacks

  • There are currently no refbacks.





Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
JIT Editorial Office, Library and Information Center, National Dong Hwa University
No. 1, Sec. 2, Da Hsueh Rd. Shoufeng, Hualien 97401, Taiwan, R.O.C.
Tel: +886-3-931-7017  E-mail: jit.editorial@gmail.com