Jung Kwansoo, Yeom Hee Gyun, Choi Daeseon

KIPS Transactions on Computer and Communication Systems, Vol. 6, No. 10, pp. 421-428, Oct. 2017
10.3745/KTCCS.2017.6.10.421,   PDF Download:
Keywords: Non-Face-to-Face, User Authentication, FinTech, Big Data, Identity Proofing
Abstract

The need for various approaches to non-face-to-face identification technology for registering and authenticating users online is being required because of the growth of online financial services and the rapid development of financial technology. In general, non-face-to-face approaches can be exposed to a greater number of threats than face-to-face approaches. Therefore, identification policies and technologies to verify users by using various factors and channels are being studied in order to complement the risks and to be more reliable non-face-to-face identification methods. One of these new approaches is to collect and verify a large number of personal information of user. Therefore, we propose a big-data based non-face-to-face Identity Proofing method that verifies identity on online based on various and large amount of information of user. The proposed method also provides an identification information management scheme that collects and verifies only the user information required for the identity verification level required by the service. In addition, we propose an identity information sharing model that can provide the information to other service providers so that user can reuse verified identity information. Finally, we prove by implementing a system that verifies and manages only the identity assurance level required by the service through the enhanced user verification in the non-face-to-face identity proofing process.

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