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A Semantic-Based K-Anonymity Scheme for Health Record Linkage

Lu, Yang, Sinnott, Richard O., Verspoor, Karin (2017) A Semantic-Based K-Anonymity Scheme for Health Record Linkage. Studies in Health Technology and Informatics, 239 . pp. 84-90. ISSN 0926-9630. (doi:10.3233/978-1-61499-783-2-84) (KAR id:80964)

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http://dx.doi.org/10.3233/978-1-61499-783-2-84

Abstract

Record linkage is a technique for integrating data from sources or providers where direct access to the data is not possible due to security and privacy considerations. This is a very common scenario for medical data, as patient privacy is a significant concern. To avoid privacy leakage, researchers have adopted k-anonymity to protect raw data from re-identification however they cannot avoid associated information loss, e.g. due to generalisation. Given that individual-level data is often not disclosed in the linkage cases, but yet remains potentially re-discoverable, we propose semantic-based linkage k-anonymity to de-identify record linkage with fewer generalisations and eliminate inference disclosure through semantic reasoning.

Item Type: Article
DOI/Identification number: 10.3233/978-1-61499-783-2-84
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software
R Medicine > R Medicine (General) > R858 Computer applications to medicine. Medical informatics. Medical information technology
T Technology
Z Bibliography. Library Science. Information Resources > ZA Information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4045 Electronic information resources
Divisions: Faculties > University wide - Teaching/Research Groups > Centre for Cyber Security Research
Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Security Group
Depositing User: Yang Lu
Date Deposited: 22 Apr 2020 19:29 UTC
Last Modified: 23 Apr 2020 10:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/80964 (The current URI for this page, for reference purposes)
Lu, Yang: https://orcid.org/0000-0002-0583-2688
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