Zero-day Malware Classification

Zero-Day Malware Classification is an academic research area within cybersecurity that focuses on the development and evaluation of methods, models, or frameworks designed to detect and categorize previously unknown malware samples that exploit vulnerabilities for which no prior signatures or patches exist.

17

Publications

1.1K

Citations

52

Authors

26

Institutions

Publications per year

2017–2026

11

Authors

52

  1. MF
    Muddassar Farooq

    National University of Computer and Emerging Sciences, Pakistan

    2 publications · 182 citations

    2

    h-index

  2. SB
    Seok-Jun Bu

    Yonsei University, South Korea

    1 publications · 261 citations

    1

    h-index

  3. DL
    Dongeun Lee

    Ulsan National Institute of Science and Technology, South Korea

    1 publications · 39 citations

    1

    h-index

  4. MZ
    Mikhail Zolotukhin

    University of Jyväskylä, Finland

    1 publications · 36 citations

    1

    h-index

  5. SC
    Shiping Chen

    Commonwealth Scientific and Industrial Research Organisation, Australia

    1 publications · 40 citations

    1

    h-index

1–5 of 52

Venues

  1. FedUni ResearchOnline (Federation University Australia)

    Repository · 1 publications · 188 citations

    1

    h-index

  2. Information Sciences

    1 publications · 261 citations

    1

    h-index

  3. IEEE Transactions on Network and Service Management

    TNSM · 1 publications · 39 citations

    1

    h-index

  4. Sensors

    1 publications · 37 citations

    1

    h-index

  5. Security and Communication Networks

    1 publications · 13 citations

    1

    h-index

1–5