Key Derivation Functions

Key Derivation Functions is a cryptographic primitive that derives one or more secret keys from a secret value such as a master key, passphrase, or shared secret, typically using a pseudorandom function to ensure key unpredictability and resistance to brute-force attacks.

37

Publications

992

Citations

110

Authors

67

Institutions

Publications per year

2017–2026

16

Authors

110

  1. LC
    Lidong Chen

    Shanghai Institute of Ceramics, China

    3 publications · 68 citations

    3

    h-index

  2. YS
    Yannick Seurin

    Agence Nationale de Sécurité du Médicament et des Produits de Santé, France

    2 publications · 24 citations

    2

    h-index

  3. YZ
    Yan Zhu

    University of Science and Technology Beijing, China

    2 publications · 69 citations

    2

    h-index

  4. DE
    David Evans

    University of Virginia, United States

    1 publications · 99 citations

    1

    h-index

  5. IE
    Israa Ezzat Salem

    Baghdad College of Economic Sciences University, Iraq

    1 publications · 13 citations

    1

    h-index

1–5 of 110

Venues

  1. IEEE Access

    3 publications · 62 citations

    3

    h-index

  2. Journal of Cryptographic Engineering

    2 publications · 71 citations

    2

    h-index

  3. IEEE Transactions on Information Theory

    2 publications · 46 citations

    2

    h-index

  4. Future Generation Computer Systems

    FGCS · 1 publications · 40 citations

    1

    h-index

  5. Computer Standards & Interfaces

    1 publications · 51 citations

    1

    h-index

1–5