research-article

Trusted third parties for secure and privacy-preserving data integration and sharing in the public sector

Authors:

Susan W. van den Braak,

Anneke ZuiderwijkAuthors Info & Claims

dg.o '12: Proceedings of the 13th Annual International Conference on Digital Government Research

Pages 135 - 144

https://doi.org/10.1145/2307729.2307752

Published: 04 June 2012 Publication History

Abstract

For public organizations data integration and sharing are important in delivering better services. However, when sensitive data are integrated and shared, privacy protection and information security become key issues. This means that information systems must be secured and that access to sensitive data must be controlled. In this paper, a framework is presented to support data sharing between public organizations for collaboration purposes. The framework focuses on solutions towards optimal data sharing and integration while ensuring the security and privacy of individuals. Data sharing is based on the need-to-know principle, that is, data are only made available when they are required to perform core processes. To facilitate this, an approach is introduced in the form of a trusted third party that manages access control to personal information and thus helps to protect the privacy of individuals. It is argued that the proposed framework is suitable for data integration and sharing on various levels. An example of best practices of data sharing in the Netherlands shows how this framework facilitates data sharing to perform knowledge transfer and other higher-level tasks.

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Cited By

Walid RJoshi KElluri L(2024)Secure and Privacy-Compliant Data Sharing: An Essential Framework for Healthcare OrganizationsProceedings of the Tenth International Conference on Mathematics and Computing10.1007/978-981-97-2066-8_2(15-26)Online publication date: 30-Jun-2024
https://doi.org/10.1007/978-981-97-2066-8_2
Li NChen ZNie JFu XJia X(2022)Complementary set encryption for privacy-preserving data consolidationInformation Sciences: an International Journal10.1016/j.ins.2022.02.002593:C(271-288)Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.ins.2022.02.002
Bastos DRibeiro JSilva FRodrigues MRabadão CFernández-Caballero ABarraca JRocha NPereira A(2021)Security Mechanisms of a Mobile Health Application for Promoting Physical Activity among Older AdultsSensors10.3390/s2121732321:21(7323)Online publication date: 3-Nov-2021
https://doi.org/10.3390/s21217323
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Index Terms

Trusted third parties for secure and privacy-preserving data integration and sharing in the public sector

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cover image ACM Other conferences

dg.o '12: Proceedings of the 13th Annual International Conference on Digital Government Research

June 2012

324 pages

ISBN:9781450314039

DOI:10.1145/2307729

Conference Chair:
John Bertot
University of Maryland
,
Program Chairs:
Luis Felipe Luna-Reyes
Universidad de las Americas, Puebla
,
Sehl Mellouli
Laval University

Copyright © 2012 ACM.

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 ACM 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]

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Elsevier
iSchool: College of Information Studies, University of Maryland
iPAC: Information Policy and Access Center

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Association for Computing Machinery

New York, NY, United States

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Published: 04 June 2012

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dg.o '12

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dg.o '12: 13th Annual International Conference on Digital Government Research

June 4 - 7, 2012

Maryland, College Park, USA

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Cited By

Walid RJoshi KElluri L(2024)Secure and Privacy-Compliant Data Sharing: An Essential Framework for Healthcare OrganizationsProceedings of the Tenth International Conference on Mathematics and Computing10.1007/978-981-97-2066-8_2(15-26)Online publication date: 30-Jun-2024
https://doi.org/10.1007/978-981-97-2066-8_2
Li NChen ZNie JFu XJia X(2022)Complementary set encryption for privacy-preserving data consolidationInformation Sciences: an International Journal10.1016/j.ins.2022.02.002593:C(271-288)Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.ins.2022.02.002
Bastos DRibeiro JSilva FRodrigues MRabadão CFernández-Caballero ABarraca JRocha NPereira A(2021)Security Mechanisms of a Mobile Health Application for Promoting Physical Activity among Older AdultsSensors10.3390/s2121732321:21(7323)Online publication date: 3-Nov-2021
https://doi.org/10.3390/s21217323
Fattah SBouguettaya A(2021)IaaS Signature Change Detection with Performance NoiseService-Oriented Computing10.1007/978-3-030-91431-8_32(516-530)Online publication date: 18-Nov-2021
https://doi.org/10.1007/978-3-030-91431-8_32
Choenni SNetten NBargh Mvan den Braak S(2021)Exploiting Big Data for Smart Government: Facing the ChallengesHandbook of Smart Cities10.1007/978-3-030-69698-6_82(1035-1057)Online publication date: 10-Jul-2021
https://doi.org/10.1007/978-3-030-69698-6_82
Choenni SNetten NBargh Mvan den Braak S(2021)Exploiting Big Data for Smart Government: Facing the ChallengesHandbook of Smart Cities10.1007/978-3-030-15145-4_82-1(1-23)Online publication date: 16-Jan-2021
https://doi.org/10.1007/978-3-030-15145-4_82-1
Bargh MChoenni SMeijer R(2020)Integrating Semi-Open Data in a Criminal Judicial SettingOpen Government10.4018/978-1-5225-9860-2.ch041(872-891)Online publication date: 2020
https://doi.org/10.4018/978-1-5225-9860-2.ch041
Fattah SBouguettaya A(2020)Event-based Detection of Changes in IaaS Performance Signatures2020 IEEE International Conference on Services Computing (SCC)10.1109/SCC49832.2020.00035(210-217)Online publication date: Nov-2020
https://doi.org/10.1109/SCC49832.2020.00035
Fattah SBouguettaya AMistry S(2020)Signature-based Selection of IaaS Cloud Services2020 IEEE International Conference on Web Services (ICWS)10.1109/ICWS49710.2020.00014(50-57)Online publication date: Oct-2020
https://doi.org/10.1109/ICWS49710.2020.00014
S. Bargh MMeijer RVink Mvan Den Braak SSchirm WChoenni S(2019)Opening Privacy Sensitive Microdata Sets in Light of GDPRProceedings of the 20th Annual International Conference on Digital Government Research10.1145/3325112.3325222(314-323)Online publication date: 18-Jun-2019
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