개인정보를 활용한 비식별정보의 유용성 측정 방법에 관한 연구
A study on the method of measuring the usefulness of De-Identified Information using Personal Information
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초록
국내외에서 개인정보의 안전한 활용을 위한 비식별 조치에 대한 관심이 높아지고 있으나 불충분한비식별 조치 및 추론 등을 통해 비식별 정보가 재식별되는 사례가 발생하고 있다. 이러한 문제점을보완하고 비식별 조치 신기술을 발굴하기 위해 비식별 정보의 안전성과 유용성을 경진하는 대회를국내와 일본에서 개최하고 있다. 본 논문은 이러한 경진대회에서 사용되고 있는 안전성과 유용성 지표를분석하고 보다 효율적으로 유용성을 측정할 수 있는 새로운 지표를 제안하고 검증하고자 한다. 비식별처리 분야에 수학 및 통계 분야의 전문가가 현저히 부족하여 많은 모집단을 통한 검증은 할 수는 없었지만 신규 지표에 대한 필요성과 타당성에 대해 매우 긍정적인 결과를 도출할 수 있었다. 우리나라의방대한 공공데이터를 비식별 정보로 안전하게 활용하기 위해서는 이러한 유용성 측정 지표에 대한연구가 꾸준히 진행되어야 하며, 본 논문을 시작으로 보다 활발한 연구가 진행되길 기대한다.
Abstract
Although interest in de-identification measures for the safe use of personal information is growing at home and abroad, cases where de-identified information is re-identified through insufficient de-identification measures and inferences are occurring. In order to compensate for these problems and discover new technologies for de-identification measures, competitions to compete on the safety and usefulness of de-identified information are being held in Korea and Japan. This paper analyzes the safety and usefulness indicators used in these competitions, and proposes and verifies new indicators that can measure usefulness more efficiently. Although it was not possible to verify through a large population due to a significant shortage of experts in the fields of mathematics and statistics in the field of de-identification processing, very positive results could be derived for the necessity and validity of new indicators. In order to safely utilize the vast amount of public data in Korea as de-identified information, research on these usefulness metrics should be continuously conducted, and it is expected that more active research will proceed starting with this thesis.
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