• Title/Summary/Keyword: 복합객체

Search Result 241, Processing Time 0.017 seconds

A study on the policy of de-identifying unstructured data for the medical data industry (의료 데이터 산업을 위한 비정형 데이터 비식별화 정책에 관한 연구)

  • Sun-Jin Lee;Tae-Rim Park;So-Hui Kim;Young-Eun Oh;Il-Gu Lee
    • Convergence Security Journal
    • /
    • v.22 no.4
    • /
    • pp.85-97
    • /
    • 2022
  • With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.