Lu, Yang, Sinnott, Richard O., Verspoor, Karin (2018) Semantic-Based Policy Composition for Privacy-Demanding Data Linkage. In: 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). . pp. 348-359. IEEE ISBN 978-1-5386-4389-1. E-ISBN 978-1-5386-4388-4. (doi:10.1109/TrustCom/BigDataSE.2018.00060) (KAR id:80961)
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Language: English 
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| Official URL: https://dx.doi.org/10.1109/TrustCom/BigDataSE.2018... |
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Abstract
Record linkage can be used to support current and future health research across populations however such approaches give rise to many challenges related to patient privacy and confidentiality including inference attacks. To address this, we present a semantic-based policy framework where linkage privacy detects attribute associations that can lead to inference disclosure issues. To illustrate the effectiveness of the approach, we present a case study exploring health data combining spatial, ethnicity and language information from several major on-going projects occurring across Australia. Compared with classic access control models, the results show that our proposal outperforms other approaches with regards to effectiveness, reliability and subsequent data utility.
University of Kent Author Information
Lu, Yang.
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 https://orcid.org/0000-0002-0583-2688
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