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Fuzzy microaggregation for the transparency principle
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0002-0368-8037
2017 (English)In: Journal of Applied Logic, ISSN 1570-8683, E-ISSN 1570-8691, Vol. 23, 70-80 p.Article in journal (Refereed) Published
Abstract [en]

Microaggregation has been proven to be an effective method for data protection in the areas of Privacy Preserving Data Mining (PPDM) and Statistical Disclosure Control (SDC). This method consists of applying a clustering method to the data set to be protected, and then replacing each of the data by the cluster representative. In this paper we propose a new method for microaggregation based on fuzzy clustering. This new approach has been defined with the main goal of being nondeterministic on the assignment of cluster centers to the original data, and at the same time being simple in its definition. Being nondeterministic permits us to overcome some of the attacks standard microaggregation suffers. 

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 23, 70-80 p.
Keyword [en]
Data privacy, Fuzzy c-means, Fuzzy clustering, Application of fuzzy sets theory, Microaggregation, Transparency attacks
National Category
Computer Science
Research subject
Skövde Artificial Intelligence Lab (SAIL)
Identifiers
URN: urn:nbn:se:his:diva-14057DOI: 10.1016/j.jal.2016.11.007ISI: 000406728700007Scopus ID: 2-s2.0-85007109704OAI: oai:DiVA.org:his-14057DiVA: diva2:1137514
Available from: 2017-08-31 Created: 2017-08-31 Last updated: 2017-08-31Bibliographically approved

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Torra, Vicenç
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