Anonymization

Anonymization is a data processing technique that irreversibly removes personally identifiable information from a dataset such that the resulting data cannot be used to re-identify individuals, thereby distinguishing it from other privacy-preserving methods that permit potential re-identification under certain conditions.

1K

Publications

67.1K

Citations

2.5K

Authors

946

Institutions

Publications per year

2017–2026

434

Authors

2.5K

  1. GL
    Grigorios Loukides

    Cardiff University, United Kingdom

    14 publications · 475 citations

    14

    h-index

  2. BC
    Benjamin C. M. Fung

    McGill University, Canada

    15 publications · 1.6K citations

    14

    h-index

  3. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    14 publications · 1.5K citations

    14

    h-index

  4. JD
    Josep Domingo‐Ferrer

    Universitat Rovira i Virgili, Spain

    14 publications · 541 citations

    13

    h-index

  5. AG
    Aris Gkoulalas-Divanis

    IBM (United States), United States

    14 publications · 435 citations

    13

    h-index

1–5 of 2.5K

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 28 publications · 4K citations

    22

    h-index

  2. arXiv (Cornell University)

    Repository · 29 publications · 920 citations

    18

    h-index

  3. IEEE Access

    22 publications · 930 citations

    16

    h-index

  4. Proceedings of the VLDB Endowment

    PVLDB · 11 publications · 1.6K citations

    11

    h-index

  5. IEEE Transactions on Dependable and Secure Computing

    TDSC · 11 publications · 537 citations

    11

    h-index

1–5