1 code implementation • International Conference on Software Engineering 2022 • Yueming Wu, Deqing Zou, Shihan Dou, Wei Yang, Duo Xu, Hai Jin
Furthermore, we conduct a case study on more than 25 million lines of code and the result indicates that VulCNN has the ability to detect large-scale vulnerability.
1 code implementation • 2 Aug 2021 • Zhen Li, Jing Tang, Deqing Zou, Qian Chen, Shouhuai Xu, Chao Zhang, Yichen Li, Hai Jin
Automatically detecting software vulnerabilities in source code is an important problem that has attracted much attention.
no code implementations • 8 Jan 2020 • Deqing Zou, Sujuan Wang, Shouhuai Xu, Zhen Li, Hai Jin
Existing vulnerability detection methods based on deep learning can detect the presence of vulnerabilities (i. e., addressing the binary classification or detection problem), but cannot pinpoint types of vulnerabilities (i. e., incapable of addressing multiclass classification).
4 code implementations • 18 Jul 2018 • Zhen Li, Deqing Zou, Shouhuai Xu, Hai Jin, Yawei Zhu, Zhaoxuan Chen
Our experiments with 4 software products demonstrate the usefulness of the framework: we detect 15 vulnerabilities that are not reported in the National Vulnerability Database.
4 code implementations • 5 Jan 2018 • Zhen Li, Deqing Zou, Shouhuai Xu, Xinyu Ou, Hai Jin, Sujuan Wang, Zhijun Deng, Yuyi Zhong
Since deep learning is motivated to deal with problems that are very different from the problem of vulnerability detection, we need some guiding principles for applying deep learning to vulnerability detection.