skip to main content
10.1145/3079452.3079490acmotherconferencesArticle/Chapter ViewAbstractPublication PagesdhConference Proceedingsconference-collections
short-paper

A Case Study of Anonymization of Medical Surveys

Published: 02 July 2017 Publication History

Abstract

Health data anonymization is a hot topic, on which both the medical and the computer science communities have made a great effort to provide a safer and trustful way of sharing data among research centers and hospitals.The main challenge in data anonymization is to provide a proper trade off between the utility of the resulting data/models and protecting individual privacy.In this paper we present a real anonymization case, with particular emphasis on choices that have to be made to carry it on, and difficulties experienced using a data set with many dimensions, and not well distinguishable features. We present our approach for evaluating disclosure risks and methods for anonymising high-dimensional medical survey data and measuring the utility of the transformed data.

References

[1]
Margareta Ciglic, Johann Eder, and Christian Koncilia. 2016. Anonymization of Data Sets with NULL Values. In Transactions on Large-Scale Data-and Knowledge- Centered Systems XXIV. Springer, 193--220.
[2]
Fida Kamal Dankar, Khaled El Emam, Angelica Neisa, and Tyson Roffey. 2012. Estimating the re-identification risk of clinical data sets. BMC medical informatics and decision making 12, 1 (2012), 66.
[3]
Gabriel Ghinita, Panagiotis Karras, Panos Kalnis, and Nikos Mamoulis. 2007. Fast data anonymization with low information loss. In Proceedings of the 33rd international conference on Very large data bases. VLDB Endowment, 758--769.
[4]
Lawrence O Gostin, Laura A Levit, Sharyl J Nass, et al. 2009. Beyond the HIPAA privacy rule: enhancing privacy, improving health through research. National Academies Press.
[5]
Vijay S Iyengar. 2002. Transforming data to satisfy privacy constraints. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 279--288.
[6]
Ashwin Machanavajjhala, Daniel Kifer, Johannes Gehrke, and Muthuramakrishnan Venkitasubramaniam. 2007. l-diversity: Privacy beyond k-anonymity. ACM Transactions on Knowledge Discovery from Data (TKDD) 1, 1 (2007), 3.
[7]
Thomas S Mayer. 2002. Privacy and confidentiality research and the US census bureau recommendations based on a review of the literature. Survey methodology (2002), 01.
[8]
Fabian Prasser and Florian Kohlmayer. 2015. Putting statistical disclosure control into practice: The ARX data anonymization tool. In Medical Data Privacy Handbook. Springer, 111--148.
[9]
Latanya Sweeney. 2002. k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10, 05 (2002), 557--570.

Cited By

View all
  • (2024)Enhancing Privacy in Healthcare: A Multilevel Approach to (Pseudo)Anonymization2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592397(1814-1819)Online publication date: 27-May-2024
  • (2023)Collecting, Processing and Secondary Using Personal and (Pseudo)Anonymized Data in Smart CitiesApplied Sciences10.3390/app1306383013:6(3830)Online publication date: 16-Mar-2023
  • (2023)Applying Differential Privacy to Medical Questionnaires2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150373(608-613)Online publication date: 13-Mar-2023
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
DH '17: Proceedings of the 2017 International Conference on Digital Health
July 2017
256 pages
ISBN:9781450352499
DOI:10.1145/3079452
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

In-Cooperation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 July 2017

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. data anonymization
  2. health privacy

Qualifiers

  • Short-paper

Conference

DH '17
DH '17: International Conference on Digital Health
July 2 - 5, 2017
London, United Kingdom

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)10
  • Downloads (Last 6 weeks)2
Reflects downloads up to 30 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Enhancing Privacy in Healthcare: A Multilevel Approach to (Pseudo)Anonymization2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592397(1814-1819)Online publication date: 27-May-2024
  • (2023)Collecting, Processing and Secondary Using Personal and (Pseudo)Anonymized Data in Smart CitiesApplied Sciences10.3390/app1306383013:6(3830)Online publication date: 16-Mar-2023
  • (2023)Applying Differential Privacy to Medical Questionnaires2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150373(608-613)Online publication date: 13-Mar-2023
  • (2022)Energy cost and accuracy impact of k-anonymity2022 International Conference on ICT for Sustainability (ICT4S)10.1109/ICT4S55073.2022.00018(65-76)Online publication date: Jun-2022
  • (2018)Large displays and tabletsProceedings of the 10th Nordic Conference on Human-Computer Interaction10.1145/3240167.3240192(664-675)Online publication date: 29-Sep-2018

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media