Polymorphic Malware Detection

Polymorphic Malware Detection is a behavioral analysis method that identifies malicious software by analyzing its dynamic execution patterns to detect variants that alter their code structure through encryption, mutation, or obfuscation techniques while preserving core functionality.

89

Publications

5.3K

Citations

230

Authors

117

Institutions

Publications per year

2017–2026

20

Authors

230

  1. YX
    Yang Xiang

    Deakin University, Australia

    5 publications · 365 citations

    5

    h-index

  2. MP
    Michalis Polychronakis

    Stony Brook University, United States

    5 publications · 211 citations

    5

    h-index

  3. SC
    Silvio Cesare

    Deakin University, Australia

    4 publications · 350 citations

    4

    h-index

  4. AH
    Andrew H. Sung

    New Mexico Institute of Mining and Technology, United States

    4 publications · 312 citations

    4

    h-index

  5. SM
    Srinivas Mukkamala

    New Mexico Institute of Mining and Technology, United States

    4 publications · 312 citations

    4

    h-index

1–5 of 230

Venues

  1. Zenodo (CERN European Organization for Nuclear Research)

    Repository · 2 publications · 92 citations

    2

    h-index

  2. International Journal of Information Security

    2 publications · 47 citations

    2

    h-index

  3. IEEE Transactions on Computers

    2 publications · 110 citations

    2

    h-index

  4. IEEE Transactions on Dependable and Secure Computing

    TDSC · 2 publications · 222 citations

    2

    h-index

  5. 1

    h-index

1–5