Machine Learning-Based Fuzz Testing Techniques: A Survey

Fuzz testing is a vulnerability discovery technique that tests the robustness of target programs by providing them with unconventional data. With the rapid increase in software quantity, scale and complexity, traditional fuzzing has revealed issues such as incomplete logic coverage, low automation l...

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主要な著者:	Ao Zhang, Yiying Zhang, Yao Xu, Cong Wang, Siwei Li
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2024-01-01
シリーズ:	IEEE Access
主題:	Vulnerability discovery fuzzing machine learning
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10374347/
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