Risk-based Data Classification

Risk-Based Data Classification is a data classification framework that categorizes information based on the level of risk associated with its unauthorized disclosure, loss, or alteration, distinguishing itself from other classification schemes by prioritizing sensitivity and potential impact on organizational assets, compliance, and operations.

15

Publications

481

Citations

47

Authors

31

Institutions

Publications per year

2017–2026

10

Authors

47

  1. AS
    Ane Sofie Böhm Nielsen

    Roche (Switzerland), Switzerland

    1 publications · 12 citations

    1

    h-index

  2. BA
    Baabak Ashuri

    Georgia Institute of Technology, United States

    1 publications · 33 citations

    1

    h-index

  3. KH
    Ke‐Wei Huang

    National University of Singapore, Singapore

    1 publications · 18 citations

    1

    h-index

  4. EZ
    Enrico Zio

    Politecnico di Milano, Italy

    1 publications · 22 citations

    1

    h-index

  5. HS
    Hiroki Sakaji

    The University of Tokyo, Japan

    1 publications · 12 citations

    1

    h-index

1–5 of 47

Venues

  1. Safety Science

    2 publications · 66 citations

    2

    h-index

  2. Pattern Recognition

    1 publications · 14 citations

    1

    h-index

  3. Therapeutic Innovation & Regulatory Science

    TIRS · 1 publications · 12 citations

    1

    h-index

  4. 1

    h-index

  5. SSRN Electronic Journal

    Repository · 1 publications · 18 citations

    1

    h-index

1–5