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An Overview of the Use of Clustering for Data Privacy

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Unsupervised Learning Algorithms

Abstract

In this chapter we review some of our results related to the use of clustering in the area of data privacy. The paper gives a brief overview of data privacy and, more specifically, on data driven methods for data privacy and discusses where clustering can be applied in this setting. We discuss the role of clustering in the definition of masking methods, and on the calculation of information loss and data utility.

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Acknowledgements

Partial support by the Spanish MEC (projects TIN2011-27076-C03-03 and TIN2014-55243-P) is acknowledged.

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Authors and Affiliations

  1. University of Skövde, Skövde, Sweden

    Vicenç Torra & Klara Stokes

  2. Universitat Autònoma de Barcelona, Barcelona, Spain

    Guillermo Navarro-Arribas

Authors
  1. Vicenç Torra
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  2. Guillermo Navarro-Arribas
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  3. Klara Stokes
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Corresponding author

Correspondence to Vicenç Torra .

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Editors and Affiliations

  1. Computer Science, Louisiana State University in Shreveport, Shreveport, Louisiana, USA

    M. Emre Celebi

  2. North American University, Houston, Texas, USA

    Kemal Aydin

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Torra, V., Navarro-Arribas, G., Stokes, K. (2016). An Overview of the Use of Clustering for Data Privacy. In: Celebi, M., Aydin, K. (eds) Unsupervised Learning Algorithms. Springer, Cham. https://doi.org/10.1007/978-3-319-24211-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-24211-8_10

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