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
Parents
31
Program-Adaptive Mutational Fuzzing
Sang Kil, Maverick Woo, David Brumley · 2015 · 239 citations · Full text
Scheduling black-box mutational fuzzing
Maverick Woo, Sang Kil, Samantha Gottlieb et al. · 2013 · 186 citations
Snipuzz: Black-box Fuzzing of IoT Firmware via Message Snippet Inference
Xiaotao Feng, Ruoxi Sun, Xiaogang Zhu et al. · 2021 · 146 citations
Fuzzing and delta-debugging SMT solvers
Robert Brummayer, Armin Biere · 2009 · 96 citations
1–5 of 31
119
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Korea Advanced Institute of Science and Technology, South Korea
2 publications · 425 citations
2
h-index
1–5 of 119
44
Carnegie Mellon University
Pittsburgh, United States
3 h-index
8 publications
1.5K citations

Chinese Academy of Sciences
Beijing, China
2 h-index
6 publications
126 citations
National University of Singapore
Singapore, Singapore
2 h-index
4 publications
316 citations

University of Central Florida
Orlando, United States
2 h-index
8 publications
392 citations
Institute of Information Engineering
Beijing, China
2 h-index
6 publications
126 citations
Tsinghua University
Beijing, China
2 h-index
8 publications
242 citations

Ajou University
Suwon, South Korea
2 h-index
4 publications
84 citations

City University of Hong Kong
Hong Kong, Hong Kong
1 h-index
1 publications
37 citations
1–8 of 44
JSA · 2 publications · 42 citations
2
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Repository · 2 publications · 31 citations
2
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Conference · 1 publications · 19 citations
1
h-index
1 publications · 35 citations
1
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PACMPL · 1 publications · 54 citations
1
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1–5