An Intelligent Fuzzing Data Generation Method Based on Deep Adversarial Learning

An Intelligent Fuzzing Data Generation Method Based on Deep Adversarial Learning

Fuzzing (Fuzz testing) can effectively identify security vulnerabilities in software by providing a large amount of unexpected input to the target program. An important part of fuzzing test is the fuzzing data generation. Numerous traditional methods to generate fuzzing data have been developed, suc...

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Bibliographic Details
Main Authors: Zhihui Li, Hui Zhao, Jianqi Shi, Yanhong Huang, Jiawen Xiong
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Automated vulnerability mining
deep adversarial learning
fuzzing
security testing
industrial security
industrial control protocol
Online Access:https://ieeexplore.ieee.org/document/8691434/

Internet

https://ieeexplore.ieee.org/document/8691434/

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