VulDeePecker: A deep learning-based system for vulnerability detection Z Li, D Zou, S Xu, X Ou, H Jin, S Wang, Z Deng, Y Zhong Proceedings of the 25th Annual Network and Distributed System Security …, 2018 | 985 | 2018 |
SySeVR: A framework for using deep learning to detect software vulnerabilities Z Li, D Zou, S Xu, H Jin, Y Zhu, Z Chen IEEE Transactions on Dependable and Secure Computing 19 (4), 2244-2258, 2022 | 582 | 2022 |
VulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection D Zou, S Wang, S Xu, Z Li, H Jin IEEE Transactions on Dependable and Secure Computing 18 (5), 2224-2236, 2021 | 279 | 2021 |
VulPecker: An automated vulnerability detection system based on code similarity analysis Z Li, D Zou, S Xu, H Jin, H Qi, J Hu Proceedings of the 32nd Annual Computer Security Applications Conference …, 2016 | 264 | 2016 |
VulDeeLocator: A Deep Learning-based Fine-grained Vulnerability Detector Z Li, D Zou, S Xu, Z Chen, Y Zhu, H Jin IEEE Transactions on Dependable and Secure Computing 19 (4), 2821-2837, 2022 | 186 | 2022 |
A comparative study of deep learning-based vulnerability detection system Z Li, D Zou, J Tang, Z Zhang, M Sun, H Jin IEEE Access 7, 103184-103197, 2019 | 104 | 2019 |
BVDetector: A program slice-based binary code vulnerability intelligent detection system J Tian, W Xing, Z Li Information and Software Technology 123, 106289, 2020 | 52 | 2020 |
Interpreting deep learning-based vulnerability detector predictions based on heuristic searching D Zou, Y Zhu, S Xu, Z Li, H Jin, H Ye ACM Transactions on Software Engineering and Methodology (TOSEM) 30 (2), 1-31, 2021 | 38 | 2021 |
RoPGen: Towards Robust Code Authorship Attribution via Automatic Coding Style Transformation Z Li, G Chen, C Chen, Y Zou, S Xu Proceedings of the 44th International Conference on Software Engineering (ICSE), 2022 | 29 | 2022 |
Automatically identifying security bug reports via multitype features analysis D Zou, Z Deng, Z Li, H Jin Proceedings of the 23rd Australasian Conference on Information Security and …, 2018 | 17 | 2018 |
SCVD: A New Semantics-Based Approach for Cloned Vulnerable Code Detection D Zou, H Qi, Z Li, S Wu, H Jin, G Sun, S Wang, Y Zhong Proceedings of the 14th International Conference on Detection of Intrusions …, 2017 | 11 | 2017 |
AutoCVSS: An Approach for Automatic Assessment of Vulnerability Severity Based on Attack Process D Zou, J Yang, Z Li, H Jin, X Ma Proceedings of the 14th International Conference on Green, Pervasive and …, 2019 | 7 | 2019 |
Generating adversarial source programs using important tokens-based structural transformations P Chen, Z Li, Y Wen, L Liu 2022 26th International Conference on Engineering of Complex Computer …, 2022 | 6 | 2022 |
基于系统调用属性的程序行为监控 李珍, 田俊峰, 杨晓晖 计算机研究与发展 49 (8), 1676-1684, 2012 | 6 | 2012 |
Investigating the Impact of Vulnerability Datasets on Deep Learning-based Vulnerability Detectors L Liu, Z Li, Y Wen, P Chen PeerJ Computer Science 8, e975, 2022 | 5 | 2022 |
Generating adversarial examples of source code classification models via q-learning-based markov decision process J Tian, C Wang, Z Li, Y Wen 2021 IEEE 21st International Conference on Software Quality, Reliability and …, 2021 | 5 | 2021 |
Towards making deep learning-based vulnerability detectors robust Z Li, J Tang, D Zou, Q Chen, S Xu, C Zhang, Y Li, H Jin arXiv preprint arXiv:2108.00669, 2021 | 5 | 2021 |
Low-cost data partitioning and encrypted backup scheme for defending against co-resident attacks J Tian, Z Wang, Z Li Eurasip journal on information security 2020, 1-14, 2020 | 5 | 2020 |
面向源代码的软件漏洞静态检测综述 李珍, 邹德清, 王泽丽, 金海 网络与信息安全学报 5 (1), 1-14, 2019 | 5 | 2019 |
A Comparative Study of Adversarial Training Methods for Neural Models of Source Code Z Li, X Huang, Y Li, G Chen Future Generation Computer Systems 142, 165-181, 2023 | 4 | 2023 |