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模糊测试×动态应用程序安全测试×
领域密码学密码学
方法族Machine learningMachine learning
起源年份19902000s
提出者Barton MillerVarious researchers
类型random input-based testing techniqueruntime vulnerability detection
开创性文献Miller, B. P., Fredriksen, L., & So, B. (1990). An empirical study of the reliability of UNIX utilities. Communications of the ACM, 33(12), 32-44. DOI ↗Kals, S., Kirda, E., Kruegel, C., & Jovanovic, N. (2006). Secubat: A web vulnerability scanner. In Proceedings of the 15th International Conference on World Wide Web (WWW 2006), pp. 247-256. DOI ↗
别名fuzz testing, fuzzer, mutation testingDAST, black-box testing, runtime security testing
相关33
摘要Fuzzing is a software testing technique that inputs large numbers of random or semi-random test cases to a program to find bugs, crashes, and security vulnerabilities. Pioneered by Barton Miller in 1990, fuzzing has become a primary method for discovering zero-day vulnerabilities in complex software. Modern fuzzing tools like libFuzzer, AFL, and HoneyPot combine coverage-guided mutation with instrumentation to efficiently explore program paths and trigger vulnerabilities. Fuzzing has discovered thousands of critical vulnerabilities in major software including browsers, compilers, and cryptographic libraries.Dynamic Application Security Testing (DAST) is a security analysis technique that tests a running application by sending various inputs and observing responses to identify vulnerabilities and security flaws. Developed in the 2000s as a complement to static analysis, DAST exercises the application at runtime, finding vulnerabilities that only manifest during execution such as authentication bypass, insecure redirects, and logic flaws. DAST is commonly used for web application testing and is considered a black-box testing approach since the tester requires no knowledge of internal code structure.
ScholarGate数据集
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  1. v1
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  3. PUBLISHED

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ScholarGate方法对比: Fuzzing · Dynamic Application Security Testing. 于 2026-06-15 检索自 https://scholargate.app/zh/compare