Disclosure Protection

Disclosure Protection is a methodological safeguard in census analysis that pertains to the systematic alteration or suppression of data outputs to prevent the identification of individual respondents while preserving the statistical utility of the dataset.

724

Publications

55.3K

Citations

1.5K

Authors

658

Institutions

Publications per year

2017–2026

176

Authors

1.5K

  1. JP
    Jerome P. Reiter

    Duke University, United States

    22 publications · 1.7K citations

    18

    h-index

  2. VT
    Vicenç Torra

    Artificial Intelligence Research Institute, Spain

    11 publications · 363 citations

    11

    h-index

  3. GT
    George T. Duncan

    Carnegie Mellon University, United States

    9 publications · 699 citations

    9

    h-index

  4. JD
    Josep Domingo‐Ferrer

    Universitat Rovira i Virgili, Spain

    8 publications · 398 citations

    8

    h-index

  5. JD
    Jörg Drechsler

    Institut für Arbeitsmarkt und Berufsforschung, Germany

    8 publications · 329 citations

    8

    h-index

1–5 of 1.5K

Venues

  1. SSRN Electronic Journal

    Repository · 29 publications · 1.8K citations

    18

    h-index

  2. Journal of the American Statistical Association

    18 publications · 1.8K citations

    16

    h-index

  3. Journal of Accounting and Economics

    12 publications · 668 citations

    12

    h-index

  4. Journal of Official Statistics

    JOS · 12 publications · 615 citations

    11

    h-index

  5. Journal of Privacy and Confidentiality

    JPC · 11 publications · 541 citations

    11

    h-index

1–5