A study on Data Context-Based Risk Measurement Method for Pseudonymized Information Processing (가명정보 처리를 위한 데이터 상황 기반의 위험도 측정방법에 관한 연구)

Dong-Hyun Kim (김동현)

doi:10.9708/jksci.2022.27.06.053

A study on Data Context-Based Risk Measurement Method for Pseudonymized Information Processing

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2022, 27(6), pp.53-63
DOI : 10.9708/jksci.2022.27.06.053
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : May 10, 2022
Accepted : June 13, 2022
Published : June 30, 2022

Dong-Hyun Kim ¹

¹한국인터넷진흥원

Accredited

ABSTRACT

Recently, as digital transformation due to the COVID-19 pandemic accelerates, data to improve individual quality of life is being used in large quantities, and more reinforced non-identification processing procedures are required to utilize the most valuable personal information among data. In Korea, procedures for de-identification measures are presented through amendments to laws and guidelines, but there is no methodology to measure the level of de-identification in the field due to ambiguous processing standards and subjective risk measurement methods. This paper compares and analyzes the current status of policy and guidelines related to de-identification measures proposed at home and abroad to derive complementary points, suggests a data context-based risk measurement method centered on pseudonymized information processing, and verifies its validity. As a result of verification through Delphi survey and focus group interview (FGI), it was confirmed that the need for the proposed methodology and the validity of the indicators were high.

KEYWORDS

BigData, Personal Information, De-Identification, Pseudonymized information, Pseudonym Risk Assesment

Citation status

* References for papers published after 2023 are currently being built.

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KJCKorea
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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

A study on Data Context-Based Risk Measurement Method for Pseudonymized Information Processing

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

A study on Data Context-Based Risk Measurement Method for Pseudonymized Information Processing

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.