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Mr X vs. Mr Y: The Emergence of Externalities in Differential Privacy

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Privacy Technologies and Policy (APF 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10518))

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Abstract

The application of differential privacy requires the addition of Laplace noise, whose level must be measured out to achieve the desired level of privacy. However, the protection of the data concerning a Mr. X, i.e., its privacy level, also depends on the other data contained in the database: a negative externality is recognized. In this paper we show that an attack on Mr. X can be conducted by an oracle, by computing the likelihood ratio under two scenarios, where the database population is made of either independent or correlated entries. We show that the target Mr. X can be spotted, notwithstanding the addition of noise, when its position happens to be eccentric with respect to the bulk of the database population.

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Author information

Authors and Affiliations

  1. Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy

    Maurizio Naldi & Giuseppe D’Acquisto

Authors
  1. Maurizio Naldi
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  2. Giuseppe D’Acquisto
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Corresponding author

Correspondence to Maurizio Naldi .

Editor information

Editors and Affiliations

  1. Centre for Legal Informatics, University of Vienna, Vienna, Austria

    Erich Schweighofer

  2. A-SIT, Graz, Austria

    Herbert Leitold

  3. European Union Agency for Network and Information Security, Heraklion, Greece

    Andreas Mitrakas

  4. Goethe University Frankfurt, Frankfurt, Hessen, Germany

    Kai Rannenberg

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Naldi, M., D’Acquisto, G. (2017). Mr X vs. Mr Y: The Emergence of Externalities in Differential Privacy. In: Schweighofer, E., Leitold, H., Mitrakas, A., Rannenberg, K. (eds) Privacy Technologies and Policy. APF 2017. Lecture Notes in Computer Science(), vol 10518. Springer, Cham. https://doi.org/10.1007/978-3-319-67280-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-67280-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67279-3

  • Online ISBN: 978-3-319-67280-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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