Behavior-based Detection

Behavior-Based Detection is a malware analysis method that identifies malicious software by monitoring and analyzing its dynamic execution behavior in a controlled environment, distinguishing it from signature-based or static analysis approaches through its reliance on observed runtime activities.

266

Publications

18.4K

Citations

813

Authors

323

Institutions

Publications per year

2017–2026

87

Authors

813

  1. CK
    Christopher Kruegel

    University of California, Santa Barbara, United States

    9 publications · 1.8K citations

    9

    h-index

  2. EK
    Engin Kirda

    Northeastern University, United States

    6 publications · 1.2K citations

    6

    h-index

  3. SJ
    Somesh Jha

    University of Wisconsin–Madison, United States

    5 publications · 660 citations

    5

    h-index

  4. MC
    Mihai Christodorescu

    University of Wisconsin–Madison, United States

    5 publications · 774 citations

    5

    h-index

  5. GV
    Giovanni Vigna

    University of California, Santa Barbara, United States

    4 publications · 701 citations

    4

    h-index

1–5 of 813

Venues

  1. IEEE Access

    8 publications · 448 citations

    8

    h-index

  2. IEEE Transactions on Dependable and Secure Computing

    TDSC · 6 publications · 650 citations

    6

    h-index

  3. Computers & Security

    6 publications · 403 citations

    6

    h-index

  4. Future Generation Computer Systems

    FGCS · 6 publications · 219 citations

    6

    h-index

  5. Security and Communication Networks

    5 publications · 92 citations

    5

    h-index

1–5