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A0753
Title: Challenges in making privacy protected data for public use Authors:  Yonghee Lee - University of Seoul (Korea, South) [presenting]
Abstract: Preserving privacy when data are disseminated for public use has been an important issue for a long time. Nowadays, privacy is more important than ever since big data and machine learning demand more and more data. We will review some experience and practice in statistical methods for disclosure limitations that research groups in Korea have considered. Also, we will introduce recent issue and challenge in privacy protection for data dissemination and synthetic data for public use in Korea.