Embedded Malware Detection

Embedded Malware Detection is a systematic method designed to identify malicious software within embedded systems by analyzing behavioral, structural, or runtime anomalies specific to resource-constrained and often real-time computing environments.

65

Publications

2.7K

Citations

189

Authors

79

Institutions

Publications per year

2017–2026

50

Authors

189

  1. HH
    Houman Homayoun

    George Mason University, United States

    7 publications · 182 citations

    7

    h-index

  2. HS
    Hossein Sayadi

    George Mason University, United States

    6 publications · 170 citations

    6

    h-index

  3. MP
    Milos Prvulović

    Georgia Institute of Technology, United States

    5 publications · 301 citations

    5

    h-index

  4. AZ
    Alenka Zajić

    Georgia Institute of Technology, United States

    5 publications · 301 citations

    5

    h-index

  5. NS
    Nader Sehatbakhsh

    Georgia Institute of Technology, United States

    5 publications · 301 citations

    5

    h-index

1–5 of 189

Venues

  1. IEEE Transactions on Computers

    4 publications · 209 citations

    4

    h-index

  2. Journal of Information Security and Applications

    JISA · 2 publications · 46 citations

    2

    h-index

  3. 2

    h-index

  4. ACM Transactions on Embedded Computing Systems

    TECS · 2 publications · 44 citations

    2

    h-index

  5. International Journal of Information Security

    1 publications · 41 citations

    1

    h-index

1–5