Entropy-based Classification

Entropy-Based Classification is a malware classification method that distinguishes malicious software based on the statistical entropy of file content, wherein high entropy values typically indicate encryption or packing behaviors characteristic of obfuscated malware.

276

Publications

13.6K

Citations

881

Authors

414

Institutions

Publications per year

2017–2026

129

Authors

881

  1. DC
    David Cuesta–Frau

    Universitat Politècnica de València, Spain

    5 publications · 96 citations

    5

    h-index

  2. SO
    Sandra Oltra–Crespo

    Universitat Politècnica de València, Spain

    3 publications · 48 citations

    3

    h-index

  3. FT
    Francisco Torrens

    Universitat de València, Spain

    3 publications · 90 citations

    3

    h-index

  4. GC
    Gloria Castellano

    Valencia Catholic University Saint Vincent Martyr, Spain

    3 publications · 90 citations

    3

    h-index

  5. PM
    Pau Miró–Martínez

    Universitat Politècnica de València, Spain

    3 publications · 48 citations

    3

    h-index

1–5 of 881

Venues

  1. Entropy

    22 publications · 700 citations

    16

    h-index

  2. IEEE Access

    6 publications · 323 citations

    8

    h-index

  3. PLoS ONE

    6 publications · 155 citations

    6

    h-index

  4. Expert Systems with Applications

    5 publications · 292 citations

    5

    h-index

  5. 4

    h-index

1–5