Design and Implementation of Vulnerability Platform Based on Knowledge Graph

被引:0
作者
Chen, Yujie [1 ]
Huang, Zaiqi [1 ]
Cao, Xudong [2 ]
Li, Xuejun [3 ]
Zhang, Yuqing [2 ,3 ]
机构
[1] Xidian Univ, HangZhou Inst Technol, Xian, Peoples R China
[2] Univ Chinese Acad Sci, Natl Comp Network Intrus Protect Ctr, Beijing, Peoples R China
[3] Xidian Univ, Sch Cyber Engn, Xian, Peoples R China
来源
2024 IEEE ANNUAL CONGRESS ON ARTIFICIAL INTELLIGENCE OF THING, AIOT 2024 | 2024年
关键词
Vulnerability platform; Knowledge graph; Fusion framework; Crawler system; Web server side;
D O I
10.1109/AIoT63253.2024.00029
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Security vulnerabilities are an important part of the cybersecurity field. These vulnerabilities are dispersed across numerous websites and forums, exhibiting multi-source heterogeneity and data redundancy, and showing a significant growth trend. This presents a challenge for the collection, sharing, and analysis of vulnerability information. To address this issue, this paper presents a novel knowledge graph-based vulnerability platform. The platform fuses the vulnerability data collected by crawlers through a knowledge graph, obtaining 1.72 times more vulnerability data than NVD, 2.05 times more than CNVD, and 4.69 times more than NSFocus. This reflects the effectiveness of knowledge graph in fusing heterogeneous vulnerability data. Furthermore, the vulnerability platform provides data services that are easily queryable and retrievable, thus facilitating the early warning and repair of security vulnerabilities.
引用
收藏
页码:99 / 104
页数:6
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