Lu, Yang, Sinnott, Richard O. (2016) Semantic-Based Privacy Protection of Electronic Health Records for Collaborative Research. In: 2016 IEEE Trustcom/BigDataSE/ISPA. . pp. 519-526. IEEE ISBN 978-1-5090-3206-8. E-ISBN 978-1-5090-3205-1. (doi:10.1109/TrustCom.2016.0105) (KAR id:80962)
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Language: English
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Official URL: https://dx.doi.org/10.1109/TrustCom.2016.0105 |
Abstract
Combined health information and web-based technologies can be used to support healthcare and research activities associated with electronic health records (EHRs). EHRs used for research purposes demand privacy, confidentiality and all information governance concerns are addressed. However, existing solutions are unable to meet the evolving research needs especially when supporting data access and linkage across organization boundaries. In this work, we show how semantic methods can aid in the specification and enforcement of policies for privacy protection. This is illustrated through a case study associated with the Australasian Diabetes Data Network (ADDN), the national paediatric type-1 diabetes data registry and the Australian Urban Research Infrastructure Network (AURIN) platform that supports Australia-wide access to urban and built environment data sets. Specifically we show that through extending the eXtensible Access Control Markup Language (XACML) with semantic capabilities, we are able to support fine-grained privacy-preserving policies leveraging semantic reasoning that is not directly available in XACML or other existing security policy specification languages.
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