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International Workshop on Data Privacy Management

International Workshop on Autonomous and Spontaneous Security

DPM 2010, SETOP 2010: Data Privacy Management and Autonomous Spontaneous Security pp 22–35Cite as

A User-Oriented Anonymization Mechanism for Public Data

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6514))

Abstract

A challenging task in privacy protection for public data is to realize an algorithm that generalizes a table according to a user’s requirement. In this paper, we propose an anonymization scheme for generating a k-anonymous table, and show evaluation results using three different tables. Our scheme is based on full-domain generalization and the requirements are automatically incorporated into the generated table. The scheme calculates the scores of intermediate tables based on user-defined priorities for attributes and selects a table suitable for the user’s requirements. Thus, the generated table meets user’s requirements and is employed in the services provided by users without any modification or evaluation.

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Author information

Authors and Affiliations

  1. KDDI R & D Laboratories Inc., 2-1-15 Ohara, Fujimino-shi, Saitama, 356-8502, Japan

    Shinsaku Kiyomoto & Toshiaki Tanaka

Authors
  1. Shinsaku Kiyomoto
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  2. Toshiaki Tanaka
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Editor information

Editors and Affiliations

  1. IT/TELECOM Bretagne, Campus de Rennes, 2 Rue de la Châtaigneraie, 35512, Cesson Sévigné, Cedex, France

    Joaquin Garcia-Alfaro

  2. IIIA-CSIC, Campus UAB, 08193, Bellaterra, Spain

    Guillermo Navarro-Arribas

  3. IT/TELECOM SudParis, 9 Rue Charles Fourier, 91011, Evry Cedex, France

    Ana Cavalli

  4. IT/TELECOM ParisTech, 46 Rue Barrault, 75634, Paris Cedex 13, France

    Jean Leneutre

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Kiyomoto, S., Tanaka, T. (2011). A User-Oriented Anonymization Mechanism for Public Data. In: Garcia-Alfaro, J., Navarro-Arribas, G., Cavalli, A., Leneutre, J. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2010 2010. Lecture Notes in Computer Science, vol 6514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19348-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-19348-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19347-7

  • Online ISBN: 978-3-642-19348-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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