Sensitive Attribute Protection

Sensitive Attribute Protection is a data privacy mechanism that specifically safeguards personally identifiable or confidential characteristics within datasets by preventing unauthorized inference, access, or disclosure of attributes deemed sensitive due to their potential for causing harm if exposed.

67

Publications

4.6K

Citations

217

Authors

116

Institutions

Publications per year

2017–2026

35

Authors

217

  1. AA
    Adeel Anjum

    COMSATS University Islamabad, Pakistan

    3 publications · 92 citations

    3

    h-index

  2. NS
    Nathan Srebro

    Toyota Technological Institute at Chicago, United States

    3 publications · 2.3K citations

    3

    h-index

  3. SU
    Saif Ur Rehman Malik

    COMSATS University Islamabad, Pakistan

    3 publications · 92 citations

    3

    h-index

  4. MB
    Miranda Bogen

    University of Southern California, United States

    2 publications · 57 citations

    2

    h-index

  5. LS
    Lili Sun

    University of Southern Queensland, Australia

    2 publications · 100 citations

    2

    h-index

1–5 of 217

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 2.3K citations

    4

    h-index

  2. Information Sciences

    3 publications · 305 citations

    3

    h-index

  3. Security and Communication Networks

    2 publications · 116 citations

    2

    h-index

  4. IEEE Access

    2 publications · 50 citations

    2

    h-index

  5. Computers & Security

    1 publications · 23 citations

    1

    h-index

1–5