Privacy Preservation

Privacy Preservation is a methodological framework within data collection ethics that ensures individual data remains confidential and inaccessible to unauthorized entities by employing techniques that prevent re-identification and unauthorized inference while enabling lawful data analysis.

1.9K

Publications

119.7K

Citations

5.1K

Authors

1.5K

Institutions

Publications per year

2017–2026

1.1K

Authors

5.1K

  1. XS
    Xuemin Shen

    University of Waterloo, Canada

    49 publications · 6.2K citations

    33

    h-index

  2. RL
    Rongxing Lu

    University of New Brunswick, Canada

    39 publications · 3.3K citations

    29

    h-index

  3. XL
    Xiaodong Lin

    University of Waterloo, Canada

    32 publications · 3.9K citations

    23

    h-index

  4. XZ
    Xuyun Zhang

    Nanjing University, China

    19 publications · 1.8K citations

    18

    h-index

  5. MG
    Mohsen Guizani

    Qatar University, Qatar

    17 publications · 1.6K citations

    16

    h-index

1–5 of 5.1K

Venues

  1. IEEE Access

    79 publications · 5.6K citations

    40

    h-index

  2. IEEE Internet of Things Journal

    68 publications · 6K citations

    39

    h-index

  3. IEEE Transactions on Industrial Informatics

    30 publications · 2.6K citations

    27

    h-index

  4. 26

    h-index

  5. Sensors

    31 publications · 1.1K citations

    23

    h-index

1–5