Attribute Inference

Attribute Inference is a type of privacy attack in which the distinguishing characteristic is the prediction of sensitive attributes not present in a dataset by exploiting patterns and correlations in auxiliary or quasi-identifying information.

137

Publications

18.5K

Citations

387

Authors

164

Institutions

Publications per year

2017–2026

73

Authors

387

  1. NZ
    Neil Zhenqiang Gong

    Duke University, United States

    9 publications · 703 citations

    9

    h-index

  2. PL
    Ping Luo

    University of Hong Kong, Hong Kong SAR China

    7 publications · 8.8K citations

    7

    h-index

  3. XT
    Xiaoou Tang

    Chinese University of Hong Kong, Hong Kong SAR China

    6 publications · 8.7K citations

    6

    h-index

  4. CC
    Chen Change Loy

    Nanyang Technological University, Singapore

    4 publications · 959 citations

    4

    h-index

  5. SZ
    Song‐Chun Zhu

    University of California, Los Angeles, United States

    3 publications · 139 citations

    3

    h-index

1–5 of 387

Venues

  1. arXiv (Cornell University)

    Repository · 22 publications · 725 citations

    16

    h-index

  2. Journal of Consumer Research

    JCR · 3 publications · 640 citations

    3

    h-index

  3. 3

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 253 citations

    2

    h-index

  5. IEEE Transactions on Network Science and Engineering

    NSE · 2 publications · 50 citations

    2

    h-index

1–5