Personalized Question Generation

Personalized Question Generation is a knowledge-based authentication method that dynamically constructs verifiable challenge questions by leveraging unique, user-specific attributes or historical data to enhance security and usability.

18

Publications

608

Citations

78

Authors

35

Institutions

Publications per year

2017–2026

13

Authors

78

  1. AS
    Anjali Singh

    University of California, Irvine, United States

    1 publications · 21 citations

    1

    h-index

  2. YL
    Yantong Lu

    Guangzhou University of Chinese Medicine, China

    1 publications · 12 citations

    1

    h-index

  3. AI
    Anca Ion

    University of Craiova, Romania

    1 publications · 16 citations

    1

    h-index

  4. YL
    Yiwen Lin

    University of California, Irvine, United States

    1 publications · 21 citations

    1

    h-index

  5. JS
    Jikang Shin

    Korea Electric Power Corporation (South Korea), South Korea

    1 publications · 21 citations

    1

    h-index

1–5 of 78

Venues

  1. IEEE Access

    2 publications · 109 citations

    2

    h-index

  2. The Electronic Journal of e-Learning

    EJEL · 1 publications · 43 citations

    1

    h-index

  3. ACM Transactions on Information Systems

    1 publications · 42 citations

    1

    h-index

  4. 1

    h-index

  5. PLoS ONE

    1 publications · 41 citations

    1

    h-index

1–5