Black-box Fuzzing

Black-Box Fuzzing is a fuzz testing methodology that generates inputs to a system without requiring knowledge of its internal structure, distinguishing itself from other fuzzing approaches by relying solely on observable external behavior to detect vulnerabilities.

31

Publications

1.6K

Citations

119

Authors

44

Institutions

Publications per year

2017–2026

21

Variants

Black-box Fuzz Testing

Authors

119

  1. CX
    Chaowei Xiao

    University of Michigan, United States

    2 publications · 35 citations

    2

    h-index

  2. CC
    Cliff C. Zou

    University of Central Florida, United States

    2 publications · 98 citations

    2

    h-index

  3. SS
    Sherri Sparks

    University of Central Florida, United States

    2 publications · 98 citations

    2

    h-index

  4. TS
    Taeshik Shon

    Ajou University, South Korea

    2 publications · 42 citations

    2

    h-index

  5. SK
    Sang Kil

    Korea Advanced Institute of Science and Technology, South Korea

    2 publications · 425 citations

    2

    h-index

1–5 of 119

Venues

  1. Journal of Systems Architecture

    JSA · 2 publications · 42 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 31 citations

    2

    h-index

  3. 1

    h-index

  4. IEEE Internet of Things Journal

    1 publications · 35 citations

    1

    h-index

  5. Proceedings of the ACM on Programming Languages

    PACMPL · 1 publications · 54 citations

    1

    h-index

1–5