• Title/Summary/Keyword: Deidentification

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Strategy Design to Protect Personal Information on Fake News based on Bigdata and Artificial Intelligence

  • Kang, Jangmook;Lee, Sangwon
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.2
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    • pp.59-66
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    • 2019
  • The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world's top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people's personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.

Deidentification Method Proposal for EHR Data on Remote Healthcare Service (원격 의료 서비스를 위한 EHR 데이터 비식별화 기법 제안)

  • Yoon, Junho;Kim, Hyunsung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.268-271
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    • 2019
  • 최근 인공지능과 빅데이터 등 최첨단 기술이 빠른 속도로 의료 정보시스템에 도입됨에 따라 환자정보를 포함한 민감한 개인정보에 대한 사이버 공격이 급증하고 있다. 다양한 개인정보 비식별화에 대한 표준이 제안되었지만, 데이터의 범주에 따른 기법 적용에 대한 연구가 미비하다. 본 논문에서는 EHR 데이터를 위한 심근경색을 대상으로 하는 원격 의료 시스템을 위한 개인정보들에 대한 민감도를 4단계로 분류하고 이에 따른 비식별화 기법에 대해 제안한다. 본 논문에서 제안한 EHR 데이터에 대한 분류 및 비식별화 기법은 다양한 의료 정보 서비스를 위한 프라이버시 보호에 활용될 수 있다.