Encrypted Data Mining

Encrypted Data Mining is a computational methodology within the field of secure data analysis that enables the extraction of meaningful patterns and knowledge from datasets while they remain encrypted, distinguishing itself from traditional data mining by preserving data confidentiality through cryptographic techniques throughout the entire mining process.

46

Publications

2.7K

Citations

145

Authors

73

Institutions

Publications per year

2017–2026

27

Authors

145

  1. MX
    Ming Xian

    National University of Defense Technology, China

    2 publications · 26 citations

    2

    h-index

  2. JL
    Jian Liu

    National University of Defense Technology, China

    2 publications · 26 citations

    2

    h-index

  3. HW
    Huimei Wang

    National University of Defense Technology, China

    2 publications · 26 citations

    2

    h-index

  4. XY
    Xun Yi

    RMIT University, Australia

    2 publications · 121 citations

    2

    h-index

  5. FL
    Flávio Luís de Mello

    Universidade Federal do Rio de Janeiro, Brazil

    2 publications · 37 citations

    2

    h-index

1–5 of 145

Venues

  1. IEEE Internet of Things Journal

    2 publications · 284 citations

    2

    h-index

  2. IEEE Access

    2 publications · 25 citations

    2

    h-index

  3. 2

    h-index

  4. Security and Communication Networks

    2 publications · 26 citations

    2

    h-index

  5. IEEE Systems Journal

    ISJ · 2 publications · 73 citations

    2

    h-index

1–5