research-article

Centralized and Distributed Anonymization for High-Dimensional Healthcare Data

Authors:

Noman Mohammed,

Benjamin C. M. Fung,

Patrick C. K. Hung,

Cheuk-Kwong LeeAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 4, Issue 4

Article No.: 18, Pages 1 - 33

https://doi.org/10.1145/1857947.1857950

Published: 01 October 2010 Publication History

Abstract

Sharing healthcare data has become a vital requirement in healthcare system management; however, inappropriate sharing and usage of healthcare data could threaten patients’ privacy. In this article, we study the privacy concerns of sharing patient information between the Hong Kong Red Cross Blood Transfusion Service (BTS) and the public hospitals. We generalize their information and privacy requirements to the problems of centralized anonymization and distributed anonymization, and identify the major challenges that make traditional data anonymization methods not applicable. Furthermore, we propose a new privacy model called LKC-privacy to overcome the challenges and present two anonymization algorithms to achieve LKC-privacy in both the centralized and the distributed scenarios. Experiments on real-life data demonstrate that our anonymization algorithms can effectively retain the essential information in anonymous data for data analysis and is scalable for anonymizing large datasets.

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Cited By

Cuzzocrea ASoufargi S(2025)Privacy-preserving multidimensional big data analytics models, methods and techniques: A comprehensive surveyExpert Systems with Applications10.1016/j.eswa.2025.126387270(126387)Online publication date: Apr-2025
https://doi.org/10.1016/j.eswa.2025.126387
Nanfack ALe Mahec GDequen G(2024)Optimizing Privacy While Limiting Information Loss in Distributed Data Anonymization2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825321(352-359)Online publication date: 15-Dec-2024
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Olatunji IRauch JKatzensteiner MKhosla M(2024)A Review of Anonymization for Healthcare DataBig Data10.1089/big.2021.016912:6(538-555)Online publication date: 1-Dec-2024
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Centralized and Distributed Anonymization for High-Dimensional Healthcare Data

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cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 4, Issue 4

October 2010

121 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/1857947

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Copyright © 2010 ACM.

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Publication History

Published: 01 October 2010

Accepted: 01 June 2010

Received: 01 January 2010

Published in TKDD Volume 4, Issue 4

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Cited By

Cuzzocrea ASoufargi S(2025)Privacy-preserving multidimensional big data analytics models, methods and techniques: A comprehensive surveyExpert Systems with Applications10.1016/j.eswa.2025.126387270(126387)Online publication date: Apr-2025
https://doi.org/10.1016/j.eswa.2025.126387
Nanfack ALe Mahec GDequen G(2024)Optimizing Privacy While Limiting Information Loss in Distributed Data Anonymization2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825321(352-359)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825321
Olatunji IRauch JKatzensteiner MKhosla M(2024)A Review of Anonymization for Healthcare DataBig Data10.1089/big.2021.016912:6(538-555)Online publication date: 1-Dec-2024
https://doi.org/10.1089/big.2021.0169
Wang RLiang JWang SChang C(2024)A divide-and-conquer approach to privacy-preserving high-dimensional big data releaseJournal of Information Security and Applications10.1016/j.jisa.2024.10375683(103756)Online publication date: Jun-2024
https://doi.org/10.1016/j.jisa.2024.103756
Aminifar AShokri MAminifar A(2024)Privacy-preserving edge Federated Learning for intelligent mobile-health systemsFuture Generation Computer Systems10.1016/j.future.2024.07.035Online publication date: Jul-2024
https://doi.org/10.1016/j.future.2024.07.035
Oishi KSei YAndrew JTahara YOhsuga A(2024) Algorithm to satisfy l ‐diversity by combining dummy records and grouping SECURITY AND PRIVACY10.1002/spy2.3737:3Online publication date: 7-Feb-2024
https://doi.org/10.1002/spy2.373
Carvalho TMoniz NFaria PAntunes L(2023)Survey on Privacy-Preserving Techniques for Microdata PublicationACM Computing Surveys10.1145/358876555:14s(1-42)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3588765
Carlson CWhite SHudnall MLochman JLaird R(2023)Leveraging Data Science to Advance Implementation Science: The Case of School Mental HealthJournal of School Health10.1111/josh.1338593:11(1045-1048)Online publication date: 14-Aug-2023
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Jadon AKumar S(2023)Leveraging Generative AI Models for Synthetic Data Generation in Healthcare: Balancing Research and Privacy2023 International Conference on Smart Applications, Communications and Networking (SmartNets)10.1109/SmartNets58706.2023.10215825(1-4)Online publication date: 25-Jul-2023
https://doi.org/10.1109/SmartNets58706.2023.10215825
Mishra SChakraborty SSahoo KBilal M(2023)Cogni-Sec: A secure cognitive enabled distributed reinforcement learning model for medical cyber–physical systemInternet of Things10.1016/j.iot.2023.10097824(100978)Online publication date: Dec-2023
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