Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

SDC Score

  • Josep Domingo-FerrerEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1502


Statistical disclosure control (SDC) methods for microdata can be ranked based on information loss, disclosure risk or a combination of both. An SDC score is a combination of information loss and disclosure risk measures used to rank methods.

Key Points

The construction of an SDC score combining information loss and disclosure risk was first proposed in [ 1, 2]. For each method M and parameterization P, the following score is computed:
$$ Score\left(\mathbf{V},\mathbf{V}^{\prime}\right) = \frac{IL\left(\mathbf{V},\mathbf{V}^{\prime}\right)+DR\left(\mathbf{V},\mathbf{V}^{\prime}\right)}{2} $$
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Recommended Reading

  1. 1.
    Domingo-Ferrer J, Mateo-Sanz JM, Torra V. Comparing SDC methods for microdata on the basis of information loss and disclosure risk. In: Proceedings of the Joint Conferences on New Techniques and Technologies for Statistics and Exchange of Technology and Know-How; 2001. p. 807–26.Google Scholar
  2. 2.
    Domingo-Ferrer J, Torra V. A quantitative comparison of disclosure control methods for microdata. In: Doyle P, Lane JI, Theeuwes JJM, Zayatz L, editors. Confidentiality, disclosure and data access: theory and practical applications for statistical agencies. Amsterdam: North-Holland; 2001. p. 111–34.Google Scholar
  3. 3.
    Yancey WE, Winkler WE, Creecy RH. Disclosure risk assessment in perturbative microdata protection. In: Domingo-Ferrer J, editor. Inference control in statistical databases, LNCS, vol. 2316. Berlin: Springer; 2002. p. 135–52.zbMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Universitat Rovira i VirgiliTarragonaSpain

Section editors and affiliations

  • Elena Ferrari
    • 1
  1. 1.DiSTAUniv. of InsubriaVareseItaly