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Keyword

fuzzing

Description: Fuzzing is an automated software testing technique that supplies varied or unexpected inputs to uncover defects and security vulnerabilities.
Wikidata ID: wiki/Q1189053
OpenAlex ID: keywords/fuzzing
An empirical study of the reliability of UNIX utilities
1990 · Barton P. Miller, Lars Fredriksen, et al. · Communications of the ACM · 1,284
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Driller: Augmenting Fuzzing Through Selective Symbolic Execution
2016 · Nick Stephens, John Grosen, et al. · Network and Distributed System Security Symposium · 912
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Evaluating Fuzz Testing
2018 · George Klees, Andrew Ruef, et al. · ACM SIGSAC Conference on Computer and Communications Security (CCS) · 657
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VUzzer: Application-aware Evolutionary Fuzzing
2017 · Sanjay Rawat, Vivek Jain, et al. · Network and Distributed System Security Symposium · 624
The Art, Science, and Engineering of Fuzzing: A Survey
2019 · Valentin J.M. Manes, HyungSeok Han, et al. · IEEE Transactions on Software Engineering · 569
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Fuzzing: Brute Force Vulnerability Discovery
2007 · Michael J. D. Sutton, Adam Greene, et al. · Medical Entomology and Zoology · 543
Fuzzing: A Survey for Roadmap
2022 · Xiaogang Zhu, Sheng Wen, et al. · ACM Computing Surveys · 341
Skyfire: Data-Driven Seed Generation for Fuzzing
2017 · Junjie Wang, Bihuan Chen, et al. · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · 338
Large Language Models Are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models
2023 · Yinlin Deng, Chunqiu Steven Xia, et al. · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · 326
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T-Fuzz: Fuzzing by Program Transformation
2018 · Hui Peng, Yan Shoshitaishvili, et al. · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · 310
AFL++ : Combining Incremental Steps of Fuzzing Research.
2020 · Andrea Fioraldi, Dominik Maier, et al. · USENIX Security Symposium · 308
Fuzzing for Software Security Testing and Quality Assurance
2008 · Ari Takanen, Jared D. DeMott, et al. · 285
Learning to Fuzz from Symbolic Execution with Application to Smart Contracts
2019 · Jingxuan He, Mislav Balunović, et al. · ACM SIGSAC Conference on Computer and Communications Security (CCS) · 284
sFuzz
2020 · Tai D. Nguyen, Long H. Pham, et al. · 279
Fuzzing: a survey
2018 · Jun Li, Bodong Zhao, et al. · Cybersecurity · 278
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Fuzzing with code fragments
2012 · Christian Holler, Kim Herzig, et al. · 274
Fuzzing: State of the Art
2018 · Hongliang Liang, Xiaoxiao Pei, et al. · IEEE Transactions on Reliability · 242
ReGuard
2018 · Chao Liu, Han Liu, et al. · 241
What You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices
2018 · Marius Muench, Jan Stijohann, et al. · Network and Distributed System Security Symposium · 219
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AV-FUZZER: Finding Safety Violations in Autonomous Driving Systems
2020 · Guanpeng Li, Yiran Li, et al. · IEEE International Symposium on Software Reliability Engineering (ISSRE) · 212
NEUZZ: Efficient Fuzzing with Neural Program Smoothing
2019 · Dongdong She, Kexin Pei, et al. · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · 210
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VerifAI: A Toolkit for the Formal Design and Analysis of Artificial Intelligence-Based Systems
2019 · Tommaso Dreossi, Daniel J. Fremont, et al. · Lecture notes in computer science · 206
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Violating Assumptions with Fuzzing
2005 · P. Oehlert · IEEE Security & Privacy · 202
FuzzBench: an open fuzzer benchmarking platform and service
2021 · Jonathan Metzman, László Szekeres, et al. · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · 201
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Ethereum Smart Contract Analysis Tools: A Systematic Review
2022 · Satpal Singh Kushwaha, Sandeep Joshi, et al. · IEEE Access · 182
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Works count: 4,281
Citation count: 35,130
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