Signature-based Malware Classification

Signature-Based Malware Classification is a malware classification method that identifies malicious software by matching predefined patterns or signatures of known malware instances against candidate samples, distinguishing it from behavioral or heuristic approaches through its reliance on static, identifiable artifacts unique to specific malware families.

54

Publications

4.3K

Citations

164

Authors

69

Institutions

Publications per year

2017–2026

28

Authors

164

  1. JR
    Junghwan Rhee

    Purdue University West Lafayette, United States

    2 publications · 37 citations

    2

    h-index

  2. PK
    Peyman Khodamoradi

    Razi University, Iran

    2 publications · 56 citations

    2

    h-index

  3. EG
    Eul Gyu Im

    Hanyang University, South Korea

    2 publications · 172 citations

    2

    h-index

  4. SS
    Sanjeev Sofat

    Punjab Engineering College, India

    2 publications · 428 citations

    2

    h-index

  5. CF
    Clint Feher

    Ben-Gurion University of the Negev, Israel

    2 publications · 365 citations

    2

    h-index

1–5 of 164

Venues

  1. Procedia Computer Science

    3 publications · 383 citations

    3

    h-index

  2. Security Informatics

    1 publications · 265 citations

    1

    h-index

  3. Information

    1 publications · 29 citations

    1

    h-index

  4. Computers & Electrical Engineering

    1 publications · 102 citations

    1

    h-index

  5. The Journal of Supercomputing

    1 publications · 32 citations

    1

    h-index

1–5