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Preservation of Utility through Hybrid k-Anonymization

  • Conference paper
Trust, Privacy, and Security in Digital Business (TrustBus 2013)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8058))

Abstract

Anonymization-based privacy protection ensures that published data cannot be linked back to an individual. The most common approach in this domain is to apply generalizations on the private data in order to maintain a privacy standard such as k-anonymity. While generalization-based techniques preserve truthfulness, relatively small output space of such techniques often results in unacceptable utility loss especially when privacy requirements are strict. In this paper, we introduce the hybrid generalizations which are formed by not only generalizations but also the data relocation mechanism. Data relocation involves changing certain data cells to further populate small groups of tuples that are indistinguishable with each other. This allows us to create anonymizations of finer granularity confirming to the underlying privacy standards. Data relocation serves as a tradeoff between utility and truthfulness and we provide an input parameter to control this tradeoff. Experiments on real data show that allowing a relatively small number of relocations increases utility with respect to heuristic metrics and query answering accuracy.

This work was funded by The Scientific and Technological Research Council of Turkey (TUBITAK) Young Researchers Career Development Program under grant 111E047.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Zirve University, Gaziantep, Turkey

    Mehmet Ercan Nergiz, Muhammed Zahit Gök & Ufuk Özkanlı

Authors
  1. Mehmet Ercan Nergiz
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  2. Muhammed Zahit Gök
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  3. Ufuk Özkanlı
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Editor information

Editors and Affiliations

  1. Centre for Security Communications and Network Research, Plymouth University, PL4 8AA, Plymouth, UK

    Steven Furnell

  2. Department of Digital Systems, University of Piraeus, 18532, Piraeus, Greece

    Costas Lambrinoudakis

  3. Computer Science Department, University of Malaga, Campus de Teatinos s/n, 29071, Malaga, Spain

    Javier Lopez

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Nergiz, M.E., Gök, M.Z., Özkanlı, U. (2013). Preservation of Utility through Hybrid k-Anonymization. In: Furnell, S., Lambrinoudakis, C., Lopez, J. (eds) Trust, Privacy, and Security in Digital Business. TrustBus 2013. Lecture Notes in Computer Science, vol 8058. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40343-9_9

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  • DOI: https://doi.org/10.1007/978-3-642-40343-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40342-2

  • Online ISBN: 978-3-642-40343-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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