금융산업에서 빅데이터 기반의 개인정보 비식별화 사용에 영향을 미치는 요인에 관한 연구 : TOE 프레임워크를 중심으로 (A Study on the Use of Big Data-based Personal Information De-identification Measures in the Financial Industry : Focused on TOE Framework)

서지정보

· 발행기관 : 한국인터넷전자상거래학회
· 수록지 정보 : 인터넷전자상거래연구 / 18권 / 3호 / 71 ~ 90페이지
· 저자명 : 우순규, 조성인, 윤수연

초록

As the 4th industrial revolution rapidly progressed and related technologies such as ICBM developed, the big data age came. Recently, the importance of personal information security has been emphasized as the number of cases of de-identification processing increases. In order to solve these two purposes of using big data and protecting personal information, the Korean government announced the “Guidelines for Personal Information De-identification Measures” in June 2016. However, due to the lack of grounds for related laws, such as the Personal Information Security Act, utilization is small.
Therefore, in order to increase the value of big data utilization, it is meaningful to identify the main factors of the personal information de-discrimination measure and to suggest the improvement plan, both academically and practically. In order to establish a research model, previous studies were examined, and a questionnaire survey was conducted mainly on financial companies for empirical analysis. The statistical package (SPSS23.0 and AMOS23.0) was used as the analysis tool to derive the results. This study will be a useful reference for companies and policy makers who want to introduce or use de-discrimination measures.

영어초록

As the 4th industrial revolution rapidly progressed and related technologies such as ICBM developed, the big data age came. Recently, the importance of personal information security has been emphasized as the number of cases of de-identification processing increases. In order to solve these two purposes of using big data and protecting personal information, the Korean government announced the “Guidelines for Personal Information De-identification Measures” in June 2016. However, due to the lack of grounds for related laws, such as the Personal Information Security Act, utilization is small.
Therefore, in order to increase the value of big data utilization, it is meaningful to identify the main factors of the personal information de-discrimination measure and to suggest the improvement plan, both academically and practically. In order to establish a research model, previous studies were examined, and a questionnaire survey was conducted mainly on financial companies for empirical analysis. The statistical package (SPSS23.0 and AMOS23.0) was used as the analysis tool to derive the results. This study will be a useful reference for companies and policy makers who want to introduce or use de-discrimination measures.

참고자료

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