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.
Heung Youl YOUM
Soonchunhyang University
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Heung Youl YOUM, "An Overview of De-Identification Techniques and Their Standardization Directions" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 7, pp. 1448-1461, July 2020, doi: 10.1587/transinf.2019ICI0002.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019ICI0002/_p
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@ARTICLE{e103-d_7_1448,
author={Heung Youl YOUM, },
journal={IEICE TRANSACTIONS on Information},
title={An Overview of De-Identification Techniques and Their Standardization Directions},
year={2020},
volume={E103-D},
number={7},
pages={1448-1461},
abstract={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.},
keywords={},
doi={10.1587/transinf.2019ICI0002},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - An Overview of De-Identification Techniques and Their Standardization Directions
T2 - IEICE TRANSACTIONS on Information
SP - 1448
EP - 1461
AU - Heung Youl YOUM
PY - 2020
DO - 10.1587/transinf.2019ICI0002
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2020
AB - 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.
ER -