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xVDB: A High-Coverage Approach for Constructing a Vulnerability Database

delete2022-01-01
delete6
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OA
AI
H
Hyunji Hong
S
Seunghoon Woo
E
Eun‐Jin Choi
J
Jihyun Choi
H
Heejo Lee *
DOI:10.1109/ACCESS.2022.3197786delete
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摘要

摘要

En 中文
Security patches play an important role in detecting and fixing one-day vulnerabilities. However, collecting abundant security patches from diverse data sources is not a simple task. This is because (1) each data source provides vulnerability information in a different way and (2) many security patches cannot be directly collected from Common Vulnerabilities and Exposures (CVE) information (e. g., National Vulnerability Database (NVD) references). In this paper, we propose a high-coverage approach that collects known security patches by tracking multiple data sources. Specifically, we considered the following three data sources: repositories (e. g., GitHub), issue trackers (e. g., Bugzilla), and Q&A sites (e. g., Stack Overflow). From the data sources, we gather even security patches that cannot be collected by considering only CVE information (i. e., previously untracked security patches). In our experiments, we collected 12,432 CVE patches from repositories and issue trackers, and 12,458 insecure posts from Q&A sites. We could collect at least four times more CVE patches than those collected in existing approaches, which demonstrates the efficacy of our approach. The collected security patches serves as a database on a public website (i. e., IoTcube) to proceed with the detection of vulnerable code clones.
Keyword:
Security
Databases
Soft sensors
Codes
Software development management
Supply chains
Open source software
Open source software
software security
vulnerability database

期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

K
Korea University
学者数:
3.6W
论文数: 3.8W
被引数: 4.4W
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