Secure Aggregation

Secure Aggregation is a cryptographic protocol in secure multi-party computation that enables a federated learning server to compute the aggregated model updates from multiple participants without revealing individual contributions, thereby preserving data privacy during collaborative model training.

487

Publications

31.8K

Citations

1.4K

Authors

569

Institutions

Publications per year

2017–2026

298

Authors

1.4K

  1. BG
    Başak Güler

    University of California, Riverside, United States

    9 publications · 804 citations

    9

    h-index

  2. JS
    Jinhyun So

    University of Southern California, United States

    9 publications · 799 citations

    9

    h-index

  3. AT
    Abdelbasset Trad

    University of Sousse, Tunisia

    7 publications · 189 citations

    7

    h-index

  4. HY
    Habib Youssef

    University of Sousse, Tunisia

    7 publications · 189 citations

    7

    h-index

  5. HA
    Hani Alzaid

    King Abdulaziz City for Science and Technology, Saudi Arabia

    6 publications · 188 citations

    6

    h-index

1–5 of 1.4K

Venues

  1. arXiv (Cornell University)

    Repository · 42 publications · 1.7K citations

    24

    h-index

  2. IEEE Internet of Things Journal

    22 publications · 2K citations

    20

    h-index

  3. IEEE Transactions on Dependable and Secure Computing

    TDSC · 12 publications · 979 citations

    12

    h-index

  4. IEEE Access

    12 publications · 534 citations

    11

    h-index

  5. IEEE Transactions on Industrial Informatics

    10 publications · 1.3K citations

    10

    h-index

1–5