김시은, 엄익채,

Vol. 34, No. 2, pp. 323-333, 4월. 2024
10.13089/JKIISC.2024.34.2.323, Full Text:
Keywords: Synthetic Data, Open Data, De-Identification, data privacy, Disclosure risk assessment
Abstract

Recently, Syntheic data has been in the spotlight as a technology that can protect personal information while maintaining the patterns and characteristics of actual data. Accordingly, technical and institutional research on synthetic data is actively being conducted, but it is difficult to actively use synthetic data due to the lack of clear standards and guidelines. This study is a preliminary study for quantifying the disclosure risk of synthetic data, and derives a privacy disclosure risk index through statistical methodology and suggests specific application measures to comply with the General Data Protection Regulation(GDPR). It is expected that the disclosure risk and the balance of data utility can be controlled through the privacy disclosure risk index of this study in an open data environment.

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