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Hiding Alice in Wonderland: A Case for the Use of Signal Processing Techniques in Differential Privacy

  • Maurizio NaldiEmail author
  • Alessandro Mazzoccoli
  • Giuseppe D’Acquisto
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11079)

Abstract

A transformation of data in statistical databases is proposed to hide the presence of an individual. The transformation employs a cascade of spectral whitening and colouring (named recolouring for brevity) that preserves the first- and second-order statistical properties of the true data (i.e. mean and correlation). A measure of practical indistinguishability is introduced for the presence of the individual to be hidden (the Impact Factor), and the transformation is applied to a toy model for the case of correlated data following a Gaussian copula model. It is shown that the Impact Factor is a multiple of what would be achieved with noise addition: the proposed recolouring transformation significantly enlarges the range of attribute values for which the presence of the individual of interest cannot be reliably inferred.

Keywords

Privacy Statistical databases Differential privacy Noise addition Correlation 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Maurizio Naldi
    • 1
    Email author
  • Alessandro Mazzoccoli
    • 1
  • Giuseppe D’Acquisto
    • 1
  1. 1.Department of Civil Engineering and Computer ScienceUniversity of Rome Tor VergataRomeItaly

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