Image-based Malware Classification

Image-Based Malware Classification is a malware classification approach that transforms executable files into visual representations, such as grayscale or color images, to leverage computer vision techniques for detecting and categorizing malicious software based on spatial patterns inherent in the converted images.

114

Publications

8.8K

Citations

344

Authors

158

Institutions

Publications per year

2017–2026

103

Authors

344

  1. MA
    Mamoun Alazab

    Charles Darwin University, Australia

    5 publications · 1.2K citations

    5

    h-index

  2. DV
    Danish Vasan

    Tsinghua University, China

    5 publications · 1.1K citations

    5

    h-index

  3. HN
    Hamad Naeem

    Sichuan University, China

    5 publications · 848 citations

    5

    h-index

  4. MR
    Muhammad Rashid Naeem

    Leshan Normal University, China

    4 publications · 353 citations

    4

    h-index

  5. FM
    Fabio Martinelli

    Institute of Informatics and Telematics, Italy

    3 publications · 64 citations

    3

    h-index

1–5 of 344

Venues

  1. Journal of Information Security and Applications

    JISA · 8 publications · 537 citations

    8

    h-index

  2. Computers & Security

    7 publications · 1.1K citations

    7

    h-index

  3. IEEE Access

    8 publications · 216 citations

    7

    h-index

  4. arXiv (Cornell University)

    Repository · 5 publications · 537 citations

    5

    h-index

  5. Sensors

    3 publications · 75 citations

    3

    h-index

1–5