Fuzzing-based Exploit Discovery
Fuzzing-Based Exploit Discovery is a vulnerability detection methodology that employs automated, randomized input generation and mutation techniques to systematically probe software systems for anomalous behaviors indicative of security flaws, distinguishing itself through its reliance on iterative fuzzing processes to uncover exploit opportunities without requiring prior knowledge of internal program logic.
14
Publications
425
Citations
58
Authors
26
Institutions
Publications per year
2017–2026
11
Parents
14
EthPloit: From Fuzzing to Efficient Exploit Generation against Smart Contracts
Qingzhao Zhang, Yizhuo Wang, Juanru Li et al. · 2020 · 67 citations
Yan Wang, Chao Zhang, Xiaobo Xiang et al. · 2018 · 64 citations
T-Reqs: HTTP Request Smuggling with Differential Fuzzing
Bahruz Jabiyev, Steven W. Sprecher, Kaan Onarlıoğlu et al. · 2021 · 38 citations
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26

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
2 h-index
9 publications
417 citations
Helmholtz Center for Information Security
Saarbrücken, Germany
2 h-index
6 publications
100 citations
NATO Cooperative Cyber Defence Centre of Excellence
Tallinn, Estonia
1 h-index
1 publications
20 citations
George Washington University
Washington, United States
1 h-index
1 publications
36 citations
Brescia University
Owensboro, United States
1 h-index
1 publications
24 citations
University of Chinese Academy of Sciences
Beijing, China
1 h-index
7 publications
448 citations

Shanghai Jiao Tong University
Shanghai, China
1 h-index
3 publications
201 citations

Pennsylvania State University
State College, United States
1 h-index
3 publications
108 citations
1–8 of 26
Repository · 2 publications · 27 citations
2
h-index
Conference · 1 publications · 36 citations
1
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1 publications · 18 citations
1
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Repository · 1 publications · 24 citations
1
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1 publications · 15 citations
1
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1–5