Statistical disclosure control for public microdata: present and future

The increasing demand from researchers and policy makers for microdata has also increased related privacy and security concerns. During the past two decades, a large volume of literature on statistical disclosure control (SDC) has been published in international journals. This review paper introduces relatively recent SDC approaches to the communities of Korean statisticians and statistical agencies. In addition to the traditional masking techniques (such as microaggregation and noise addition), we introduce an online analytic system, differential privacy, and synthetic data. For each approach, the application example (with pros and cons, as well as methodology) is highlighted, so that the paper can assist statical agencies that seek a practical SDC approach.