Articles producció científicaEnginyeria Informàtica i Matemàtiques

Database Reconstruction Is Not So Easy and Is Different from Reidentification

  • Identification data

    Identifier:  imarina:9385381
    Authors:  Muralidhar, K; Domingo-Ferrer, J
    Abstract:
    In recent years, it has been claimed that releasing accurate statistical information on a database is likely to allow its complete reconstruction. Differential privacy has been suggested as the appropriate methodology to prevent these attacks. These claims have recently been taken very seriously by the U.S. Census Bureau and led them to adopt differential privacy for releasing U.S. Census data. This in turn has caused consternation among users of the Census data due to the lack of accuracy of the protected outputs. It has also brought legal action against the U.S. Department of Commerce. In this article, we trace the origins of the claim that releasing information on a database automatically makes it vulnerable to being exposed by reconstruction attacks and we show that this claim is, in fact, incorrect. We also show that reconstruction can be averted by properly using traditional statistical disclosure control (SDC) techniques. We further show that the geographic level at which exact counts are released is even more relevant to protection than the actual SDC method employed. Finally, we caution against confusing reconstruction and reidentification: using the quality of reconstruction as a metric of reidentification results in exaggerated reidentification risk figures.
  • Others:

    Link to the original source: https://journals.sagepub.com/doi/abs/10.2478/jos-2023-0017
    APA: Muralidhar, K; Domingo-Ferrer, J (2023). Database Reconstruction Is Not So Easy and Is Different from Reidentification. Journal of Official Statistics, 39(3), 381-398. DOI: 10.2478/jos-2023-0017
    Paper original source: Journal of Official Statistics. 39 (3): 381-398
    Article's DOI: 10.2478/jos-2023-0017
    Journal publication year: 2023-09-01
    Entity: Universitat Rovira i Virgili
    Paper version: info:eu-repo/semantics/publishedVersion
    Record's date: 2026-05-09
    URV's Author/s: Domingo Ferrer, Josep
    Department: Enginyeria Informàtica i Matemàtiques
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Publication Type: Journal Publications
    Author, as appears in the article.: Muralidhar, K; Domingo-Ferrer, J
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Thematic Areas: Statistics and probability, Statistics & probability, Social statistics and informatics, Social sciences, mathematical methods, Matemática / probabilidade e estatística, General o multidisciplinar, Engenharias iii, Educação, Ciencias sociales
    Author's mail: josep.domingo@urv.cat, josep.domingo@urv.cat, josep.domingo@urv.cat, josep.domingo@urv.cat
  • Keywords:

    Statistical disclosure control
    Security
    Privac
    Differential privacy
    Differential privac
    Database reconstruction
    Database privacy
    Social Sciences
    Mathematical Methods
    Statistics & Probability
    Statistics and Probability
    Social statistics and informatics
    Matemática / probabilidade e estatística
    General o multidisciplinar
    Engenharias iii
    Educação
    Ciencias sociales
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