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A Study on the Quantified Point System for Designation of Personal Identity Proofing Service Provider based on Resident Registration Number

  • Kim, JongBae (Department of Software Engineering, Sejong Cyber University)
  • Received : 2022.09.18
  • Accepted : 2022.09.24
  • Published : 2022.12.31

Abstract

In this paper, we propose to improve the designation examination criteria of agencies that provide personal identity proofing based on the resident registration number (RRN), a 13-digit number uniquely assigned by the government to identify Korean citizens. In online commerce, etc., the personal identity proofing agency (PIPA) is a place where online users can prove their personal identity by presenting an alternative means instead of their RRN. The designation examination criteria for PIPAs established in 2012 is a revision of the relevant current laws, and there is a problem in applying the designation examination for alternative means of RRN as the current examination standard. Therefore, in this paper, we propose a method to make the current examination criteria applicable to the newly designated examination of the personal identity proofing service provider based on the current RRN alternative method. According to the current designation examination criteria, only those who satisfy all the examination criteria are designated as the PIPA. However, in reality, it is not in line with the purpose of regulatory reform to require that all examination criteria be satisfied. In the proposed method, it is proposed to apply the standard score system for designation of PIPAs, to make the law current, to secure legal compliance, and to establish a new examination standard to provide a new alternative means of personal identity proofing service. By applying the proposed method to the PIPA designation examination, various alternative means of RRN can be utilized in the online commerce service market.

Keywords

Acknowledgement

An extended version of this paper has been published at the ISAAC 2022 conference[9], and this work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2020R1F1A106890011)

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