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Edit Constraints on Microaggregation and Additive Noise

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Book cover Privacy and Security Issues in Data Mining and Machine Learning (PSDML 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6549))

Abstract

Privacy preserving data mining and statistical disclosure control propose several perturbative methods to protect the privacy of the respondents. Such perturbation can introduce inconsistencies to the sensitive data. Due to this, data editing techniques are used in order to ensure the correctness of the collected data before and after the anonymization.

In this paper we propose a methodology to protect microdata based on noise addition that takes data edits into account. Informally, when adding noise causes a constraint to fail, we apply a process of noise swapping to preserve the edit constraint. We check its suitability against the constrained microaggregation, a method for microaggregation that avoids the introduction of such inconsistencies.

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Author information

Authors and Affiliations

  1. Artificial Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC), Campus UAB, Catalonia, Spain

    Isaac Cano & Vicenç Torra

Authors
  1. Isaac Cano
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  2. Vicenç Torra
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Editor information

Editors and Affiliations

  1. Johann Wolfgang Goethe University, Ruth-Moufang-Str. 1, 60438, Frankfurt am Main, Germany

    Christos Dimitrakakis

  2. Information Analytics Lab, IBM Research – Zurich, Säumerstrasse 4, 8803, Rüschlikon, Switzerland

    Aris Gkoulalas-Divanis

  3. Ecole Polytechnice Fédérale de Lausanne, I&C - ISC - LASEC, Bâtiment INF, Station 14, CH-1015, Lausanne, Switzerland

    Aikaterini Mitrokotsa

  4. Department of Computer and Communication Engineering, University of Thessaly, Glavani 37 & 28TH, GR 38221, Octovriou, Volos, Greece

    Vassilios S. Verykios

  5. Faculty of Engineering and Natural Sciences, Sabanci University, Orhanli, 34956, Tuzla, Istanbul, Turkey

    Yücel Saygin

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© 2011 Springer-Verlag Berlin Heidelberg

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Cano, I., Torra, V. (2011). Edit Constraints on Microaggregation and Additive Noise. In: Dimitrakakis, C., Gkoulalas-Divanis, A., Mitrokotsa, A., Verykios, V.S., Saygin, Y. (eds) Privacy and Security Issues in Data Mining and Machine Learning. PSDML 2010. Lecture Notes in Computer Science(), vol 6549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19896-0_1

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  • DOI: https://doi.org/10.1007/978-3-642-19896-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19895-3

  • Online ISBN: 978-3-642-19896-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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