A Privacy Protection Model for Patient Data with Multiple Sensitive Attributes

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dc.contributor.authorGal, Tamas S.
dc.contributor.authorChen, Zhiyuan
dc.contributor.authorGangopadhyay, Aryya
dc.date.accessioned2021-08-16T18:37:07Z
dc.date.available2021-08-16T18:37:07Z
dc.date.issued2008-07
dc.description.abstractThe identity of patients must be protected when patient data are shared. The two most commonly used models to protect identity of patients are L-diversity and K-anonymity. However, existing work mainly considers data sets with a single sensitive attribute, while patient data often contain multiple sensitive attributes (e.g., diagnosis and treatment). This article shows that although the K-anonymity model can be trivially extended to multiple sensitive attributes, the L-diversity model cannot. The reason is that achieving L-diversity for each individual sensitive attribute does not guarantee L-diversity over all sensitive attributes. We propose a new model that extends L-diversity and K-anonymity to multiple sensitive attributes and propose a practical method to implement this model. Experimental results demonstrate the effectiveness of our approach.en_US
dc.description.urihttps://www.igi-global.com/article/privacy-protection-model-patient-data/2485en_US
dc.format.extent17 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2oa0w-ujuz
dc.identifier.citationGal, Tamas; Chen, Zhiyuan; Gangopadhyay, Aryya; A Privacy Protection Model for Patient Data with Multiple Sensitive Attributes; International Journal of Information Security and Privacy (IJISP) 2(3), 28-44, July 2008; https://doi.org/10.4018/jisp.2008070103en_US
dc.identifier.urihttps://doi.org/10.4018/jisp.2008070103
dc.identifier.urihttp://hdl.handle.net/11603/22463
dc.language.isoen_USen_US
dc.publisherIGI Globalen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.titleA Privacy Protection Model for Patient Data with Multiple Sensitive Attributesen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-6984-7248en_US

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