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mHealth: A privacy threat analysis for public health surveillance systems
Department of Mathematics and Computer Science, Karlstad University, Sweden.
Department of Mathematics and Computer Science, Karlstad University, Sweden.
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Information Systems)ORCID iD: 0000-0002-8607-948X
Department of Mathematics and Computer Science, Karlstad Universitet, Sweden.
2018 (English)In: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), (2018) / [ed] B Kane, J Hollmen, C McGregor, P Soda, IEEE , 2018, p. 42-47Conference paper, Published paper (Refereed)
Abstract [en]

Community Health Workers (CHWs) have been usingMobile Health Data Collection Systems (MDCSs) for supportingthe delivery of primary healthcare and carrying out public healthsurveys, feeding national-level databases with families’ personaldata. Such systems are used for public surveillance and to managesensitive data (i.e., health data), so addressing the privacy issuesis crucial for successfully deploying MDCSs. In this paper wepresent a comprehensive privacy threat analysis for MDCSs,discuss the privacy challenges and provide recommendationsthat are specially useful to health managers and developers. Weground our analysis on a large-scale MDCS used for primarycare (GeoHealth) and a well-known Privacy Impact Assessment(PIA) methodology. The threat analysis is based on a compilationof relevant privacy threats from the literature as well as brainstormingsessions with privacy and security experts. Among themain findings, we observe that existing MDCSs do not employadequate controls for achieving transparency and interveinability.Thus, threatening fundamental privacy principles regarded asdata quality, right to access and right to object. Furthermore, itis noticeable that although there has been significant research todeal with data security issues, the attention with privacy in itsmultiple dimensions is prominently lacking.

Place, publisher, year, edition, pages
IEEE , 2018. p. 42-47
Series
IEEE Symposium on Computer-Based Medical Systems, ISSN 1063-7125, E-ISSN 2372-9198
Keywords [en]
mHealth, privac, data protection, threat analysis, mHealth data collection system, public healthcare
National Category
Computer and Information Sciences
Research subject
INF303 Information Security; Information Systems
Identifiers
URN: urn:nbn:se:his:diva-16431DOI: 10.1109/CBMS.2018.00015Scopus ID: 2-s2.0-85050971478ISBN: 978-1-5386-6061-4 (print)OAI: oai:DiVA.org:his-16431DiVA, id: diva2:1265565
Conference
31st IEEE International Symposium on Computer-Based Medical Systems, CBMS 2018; Karlstad; Sweden; 18 June 2018 through 21 June 2018
Available from: 2018-11-24 Created: 2018-11-24 Last updated: 2019-02-08Bibliographically approved

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Åhlfeldt, Rose-Mharie

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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  • sv-SE
  • Other locale
More languages
Output format
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