Multi-class Malware Classification

Multi-Class Malware Classification is a malware analysis task that involves categorizing malicious software into one of several predefined distinct classes based on shared behavioral, structural, or code-level characteristics, distinguishing it from binary or hierarchical classification approaches by enabling fine-grained discrimination across multiple malware families simultaneously.

19

Publications

842

Citations

82

Authors

37

Institutions

Publications per year

2017–2026

17

Authors

82

  1. YL
    Yan Luo

    University of Massachusetts Lowell, United States

    1 publications · 52 citations

    1

    h-index

  2. VV
    Vinita Verma

    University of Delhi, India

    1 publications · 76 citations

    1

    h-index

  3. MA
    Mohamad Al Kadri

    American University of Beirut, Lebanon

    1 publications · 17 citations

    1

    h-index

  4. SQ
    Sirajuddin Qureshi

    Beijing University of Technology, China

    1 publications · 25 citations

    1

    h-index

  5. ZQ
    Zisen Qi

    Air Force Engineering University, China

    1 publications · 13 citations

    1

    h-index

1–5 of 82

Venues

  1. IEEE Access

    3 publications · 128 citations

    3

    h-index

  2. Computers & Security

    2 publications · 141 citations

    2

    h-index

  3. Applied Sciences

    2 publications · 43 citations

    2

    h-index

  4. 1

    h-index

  5. Procedia Computer Science

    1 publications · 30 citations

    1

    h-index

1–5