Private Data Publishing

Private Data Publishing is a methodological framework within the field of data privacy that enables the release of datasets or statistical summaries while formally guaranteeing individual privacy through the incorporation of controlled noise or perturbation mechanisms, typically governed by differential privacy principles.

124

Publications

9K

Citations

338

Authors

166

Institutions

Publications per year

2017–2026

48

Authors

338

  1. RC
    Rui Chen

    Hong Kong Baptist University, Hong Kong SAR China

    11 publications · 1.3K citations

    11

    h-index

  2. NL
    Ninghui Li

    Purdue University West Lafayette, United States

    9 publications · 958 citations

    9

    h-index

  3. BC
    Benjamin C. M. Fung

    McGill University, Canada

    7 publications · 519 citations

    7

    h-index

  4. NM
    Noman Mohammed

    University of Manitoba, Canada

    5 publications · 491 citations

    5

    h-index

  5. XX
    Xiaokui Xiao

    Nanyang Technological University, Singapore

    5 publications · 1.6K citations

    5

    h-index

1–5 of 338

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 171 citations

    5

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 4 publications · 489 citations

    4

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 513 citations

    4

    h-index

  4. Knowledge-Based Systems

    3 publications · 181 citations

    3

    h-index

  5. IEEE Transactions on Dependable and Secure Computing

    TDSC · 3 publications · 160 citations

    3

    h-index

1–5