ArticleInternational journal of health geographics2016
Anonymisation of geographical distance matrices via Lipschitz embedding.
Article in International journal of health geographics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- The Effectiveness of Novel E-Health Applications in the Prevention and Management of Childhood Obesity.Hormone research in paediatrics · 2026Article
- Locational privacy-preserving distance computations with intersecting sets of randomly labeled grid points.International journal of health geographics · 2021Article
- Novel e-Health Applications for the Management of Cardiometabolic Risk Factors in Children and Adolescents in Greece.Nutrients · 2020Review
- Using mobile location data in biomedical research while preserving privacy.Journal of the American Medical Informatics Association : JAMIA · 2018Article
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2 authors.
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Abstract
backgroundAnonymisation of spatially referenced data has received increasing attention in recent years. Whereas the research focus has been on the anonymisation of point locations, the disclosure risk arising from the publishing of inter-point distances and corresponding anonymisation methods have not been studied systematically.
methodsWe propose a new anonymisation method for the release of geographical distances between records of a microdata file--for example patients in a medical database. We discuss a data release scheme in which microdata without coordinates and an additional distance matrix between the corresponding rows of the microdata set are released. In contrast to most other approaches this method preserves small distances better than larger distances. The distances are modified by a variant of Lipschitz embedding.
resultsThe effects of the embedding parameters on the risk of data disclosure are evaluated by linkage experiments using simulated data. The results indicate small disclosure risks for appropriate embedding parameters.
conclusionThe proposed method is useful if published distance information might be misused for the re-identification of records. The method can be used for publishing scientific-use-files and as an additional tool for record-linkage studies.
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