Inference Privacy

Inference Privacy is a privacy-preserving framework that belongs to the class of edge privacy mechanisms, distinguished by its focus on preventing unauthorized inference of sensitive information from data or model outputs in edge computing environments through obfuscation, perturbation, or access control techniques.

65

Publications

2.2K

Citations

242

Authors

114

Institutions

Publications per year

2017–2026

49

Authors

242

  1. WP
    Wee Peng Tay

    Nanyang Technological University, Singapore

    5 publications · 161 citations

    5

    h-index

  2. MS
    Meng Sun

    Nanyang Technological University, Singapore

    4 publications · 148 citations

    4

    h-index

  3. MA
    Murali Annavaram

    University of Southern California, United States

    3 publications · 95 citations

    3

    h-index

  4. ZW
    Zhibo Wang

    Wuhan University, China

    3 publications · 139 citations

    3

    h-index

  5. YW
    Yongqin Wang

    Chongqing University, China

    2 publications · 78 citations

    2

    h-index

1–5 of 242

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 216 citations

    7

    h-index

  2. 5

    h-index

  3. IEEE Internet of Things Journal

    2 publications · 111 citations

    2

    h-index

  4. IEEE Intelligent Systems

    1 publications · 21 citations

    1

    h-index

  5. Proceedings of the VLDB Endowment

    PVLDB · 1 publications · 88 citations

    1

    h-index

1–5