Attribute Inference Attacks

Attribute Inference Attack is a type of privacy attack in which an adversary exploits observable data and auxiliary information to predict sensitive attributes that are not directly accessible, distinguishing itself from other inference attacks by focusing on the reconstruction of specific hidden attributes rather than overall data re-identification or membership status.

52

Publications

4.8K

Citations

154

Authors

65

Institutions

Publications per year

2017–2026

38

Authors

154

  1. NZ
    Neil Zhenqiang Gong

    Duke University, United States

    5 publications · 337 citations

    5

    h-index

  2. SJ
    Somesh Jha

    University of Wisconsin–Madison, United States

    3 publications · 950 citations

    3

    h-index

  3. HY
    Hongzhi Yin

    The University of Queensland, Australia

    3 publications · 234 citations

    3

    h-index

  4. MF
    Matt Fredrikson

    Carnegie Mellon University, United States

    3 publications · 950 citations

    3

    h-index

  5. IG
    Irene Giacomelli

    University of Florence, Italy

    3 publications · 950 citations

    3

    h-index

1–5 of 154

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 421 citations

    11

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 253 citations

    2

    h-index

  3. IEEE Transactions on Network Science and Engineering

    NSE · 2 publications · 50 citations

    2

    h-index

  4. Journal of Computer Security

    1 publications · 35 citations

    1

    h-index

  5. IEEE Access

    1 publications · 20 citations

    1

    h-index

1–5