A Vulnerability Risk Assessment Method Based on Heterogeneous Information Network

被引:9
|
作者
Wang, Wenrui [1 ]
Shi, Fan [1 ]
Zhang, Min [1 ]
Xu, Chengxi [1 ]
Zheng, Jinghua [1 ]
机构
[1] Natl Univ Def Technol, Coll Elect Engn, Hefei 230037, Peoples R China
关键词
Risk management; Measurement; Security; Computational modeling; Communication networks; Dispersion; Semantics; Common vulnerability scoring systems (CVSS); vulnerability; risk assessment; information fusion; heterogeneous information network;
D O I
10.1109/ACCESS.2020.3015551
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the increasing number of network security vulnerabilities, vulnerability risk assessment must be performed to prioritize the repair of high-risk vulnerabilities. Traditional vulnerability risk assessment is based primarily on the Common Vulnerability Scoring Systems (CVSS) and attack graphs. Nevertheless, the CVSS metrics ignore the impact of the vulnerability on the specific network, which accounts that the identical vulnerability exists in different network environments is assigned repeated values. Additionally, the attack graphs still suffer from scalability and readability issues. To solve the above problems, a ranking method based on the heterogeneous information network is innovatively proposed to assess the vulnerability risk in a specific network. It considers the exploitability of a vulnerability, the impact of a vulnerability on the network components, and the importance of the vulnerable components. First, a heterogeneous information network containing vulnerability and host and the relationships between host and host is constructed to compute the risk score for each vulnerability and implement the ranking process. Second, a model extension method is proposed to adapt to situations in which additional factors related to vulnerability risk assessment need to be considered. Finally, we explore two case studies to compare the proposed method with CVSS and attack graph-based methods. The simulation results show that the proposed method can accurately assess the risk of vulnerabilities in a specific network environment and that it has a lower computational complexity than other methods.
引用
收藏
页码:148315 / 148330
页数:16
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