Software Vulnerability Analysis and Discovery Using Deep Learning Techniques: A Survey-Reference-Cited by-同舟云学术

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Software Vulnerability Analysis and Discovery Using Deep Learning Techniques: A Survey

Published:2020 Issue: Volume:8 Page:197158-197172
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zeng Peng,Lin Guanjun^ORCID,Pan Lei^ORCID,Tai Yonghang^ORCID,Zhang Jun

Funder

Optoelectronic Information Technology Key Laboratory Open Project Fund of Yunnan Province, China

2019 Educational Research Project of Fujian Province, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09244140.pdf?arnumber=9244140

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Vulnerabilities and Security Patches Detection in OSS: A Survey;ACM Computing Surveys;2024-09-09

2. An empirical study on the impact of graph representations for code vulnerability detection using graph learning;2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR);2024-08-15

3. Defect-scanner: a comparative empirical study on language model and deep learning approach for software vulnerability detection;International Journal of Information Security;2024-08-13

4. Explaining poor performance of text-based machine learning models for vulnerability detection;Empirical Software Engineering;2024-07-22

5. Automating shareable cyber threat intelligence production for closed source software vulnerabilities: a deep learning based detection system;International Journal of Information Security;2024-07-08

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