An Overview of De-Identification Techniques and Their Standardization Directions

被引:9
作者
Youm, Heung Youl [1 ]
机构
[1] Soonchunhyang Univ, Dept Informat Secur Engn, Asan, South Korea
关键词
de-identification; re-identification; pseudonym; anonymization; standardization; DIFFERENTIAL PRIVACY; ANONYMITY;
D O I
10.1587/transinf.2019ICI0002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
De-identification [1]-[5], [30]-[71] is the process that organizations can use to remove personal information from data that they collect, use, archive, and share with other organizations. It is recognized as an important tool for organizations to balance requirements between the use of data and privacy protection of personal information. Its objective is to remove the association between a set of identifying attributes and the data principal where identifying attribute is attribute in a dataset that is able to contribute to uniquely identifying a data principal within a specific operational context and data principal is entity to which data relates. This paper provides an overview of de-identification techniques including the data release models. It also describes the current standardization activities by the standardization development organizations in terms of de-identification. It suggests future standardization directions including potential future work items.
引用
收藏
页码:1448 / 1461
页数:14
相关论文
共 50 条
[31]   An interaction model for de-identification of human data held by external custodians [J].
Simmons, Andrew J. ;
Curumsing, Maheswaree Kissoon ;
Vasa, Rajesh .
PROCEEDINGS OF THE 30TH AUSTRALIAN COMPUTER-HUMAN INTERACTION CONFERENCE (OZCHI 2018), 2018, :23-31
[32]   Efficient Recommendation of De-Identification Policies Using MapReduce [J].
Ding, Xiaofeng ;
Wang, Li ;
Shao, Zhiyuan ;
Jin, Hai .
IEEE TRANSACTIONS ON BIG DATA, 2019, 5 (03) :343-354
[33]   Medical Image De-Identification using Cloud Services [J].
Kopchick, B. ;
Klenk, J. ;
Carlson, T. ;
Kumpatla, M. ;
Klimov, S. ;
Mikdadi, D. ;
Pan, Q. ;
Gustafson, S. ;
Kaltman, J. ;
Wagner, U. ;
Clunie, D. ;
Farahani, K. .
MEDICAL IMAGING 2022: IMAGING INFORMATICS FOR HEALTHCARE, RESEARCH, AND APPLICATIONS, 2022, 12037
[34]   An open source toolkit for medical imaging de-identification [J].
David Rodríguez González ;
Trevor Carpenter ;
Jano I. van Hemert ;
Joanna Wardlaw .
European Radiology, 2010, 20 :1896-1904
[35]   Selling Health Data De-Identification, Privacy, and Speech [J].
Kaplan, Bonnie .
CAMBRIDGE QUARTERLY OF HEALTHCARE ETHICS, 2015, 24 (03) :256-271
[36]   An open source toolkit for medical imaging de-identification [J].
Rodriguez Gonzalez, David ;
Carpenter, Trevor ;
van Hemert, Jano I. ;
Wardlaw, Joanna .
EUROPEAN RADIOLOGY, 2010, 20 (08) :1896-1904
[37]   De-identification of patient notes with recurrent neural networks [J].
Dernoncourt, Franck ;
Lee, Ji Young ;
Uzuner, Ozlem ;
Szolovits, Peter .
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2017, 24 (03) :596-606
[38]   Impact Analysis of De-Identification in Clinical Notes Classification [J].
Baumgartner, Martin ;
Schreier, Guenter ;
Hayn, Dieter ;
Kreiner, Karl ;
Haider, Lukas ;
Wiesmueller, Fabian ;
Brunelli, Luca ;
Poelzl, Gerhard .
DHEALTH 2022-PROCEEDINGS OF THE 16TH HEALTH INFORMATICS MEETS DIGITAL HEALTH CONFERENCE, 2022, 293 :189-196
[39]   Face image de-identification based on feature embedding [J].
Hanawa, Goki ;
Ito, Koichi ;
Aoki, Takafumi .
EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, 2024, 2024 (01)
[40]   Verification of De-Identification Techniques for Personal Information Using Tree-Based Methods with Shapley Values [J].
Lee, Junhak ;
Jeong, Jinwoo ;
Jung, Sungji ;
Moon, Jihoon ;
Rho, Seungmin .
JOURNAL OF PERSONALIZED MEDICINE, 2022, 12 (02)