Encrypted Federated Learning

Encrypted Federated Learning is a federated learning framework that integrates cryptographic encryption techniques to secure model updates during transmission and computation, thereby preserving data privacy while enabling collaborative model training across decentralized clients.

14

Publications

849

Citations

89

Authors

47

Institutions

Publications per year

2017–2026

14

Authors

89

  1. AQ
    Attia Qammar

    University of Science and Technology Beijing, China

    1 publications · 51 citations

    1

    h-index

  2. JG
    Jin Gu

    University of Science and Technology Beijing, China

    1 publications · 140 citations

    1

    h-index

  3. GL
    Guoxiu Liu

    Nanjing University of Posts and Telecommunications, China

    1 publications · 18 citations

    1

    h-index

  4. RT
    Rana Tallal Javed

    Information Technology University, Pakistan

    1 publications · 13 citations

    1

    h-index

  5. TH
    Tianqi Han

    Zhejiang University, China

    1 publications · 33 citations

    1

    h-index

1–5 of 89

Venues

  1. Computer Methods and Programs in Biomedicine

    1 publications · 17 citations

    1

    h-index

  2. Information Fusion

    1 publications · 58 citations

    1

    h-index

  3. IEEE Transactions on Network and Service Management

    TNSM · 1 publications · 18 citations

    1

    h-index

  4. Information Sciences

    1 publications · 140 citations

    1

    h-index

  5. Medical Image Analysis

    1 publications · 82 citations

    1

    h-index

1–5