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Network Security Node-Edge Scoring System Using Attack Graph Based on Vulnerability Correlationopen access

Authors
Shin, Gun-YoonHong, Sung-SamLee, Jung-SikHan, In-SungKim, Hwa-KyungOh, Haeng-Rok
Issue Date
Jul-2022
Publisher
MDPI
Keywords
network security; common vulnerability scoring system; scoring system; vulnerability correlation analysis; attack graph
Citation
APPLIED SCIENCES-BASEL, v.12, no.14
Journal Title
APPLIED SCIENCES-BASEL
Volume
12
Number
14
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/85578
DOI
10.3390/app12146852
ISSN
2076-3417
Abstract
As network technology has advanced, and as larger and larger quantities of data are being collected, networks are becoming increasingly complex. Various vulnerabilities are being identified in such networks, and related attacks are continuously occurring. To solve these problems and improve the overall quality of network security, a network risk scoring technique using attack graphs and vulnerability information must be used. This technology calculates the degree of risk by collecting information and related vulnerabilities in the nodes and the edges existing in the network-based attack graph, and then determining the degree of risk in a specific network location or the degree of risk occurring when a specific route is passed within the network. However, in most previous research, the risk of the entire route has been calculated and evaluated based on node information, rather than edge information. Since these methods do not include correlations between nodes, it is relatively difficult to evaluate the risk. Therefore, in this paper, we propose a vulnerability Correlation and Attack Graph-based node-edge Scoring System (VCAG-SS) that can accurately measure the risk of a specific route. The proposed method uses the Common Vulnerability Scoring System (CVSS) along with node and edge information. Performing the previously proposed arithmetic evaluation of confidentiality, integrity, and availability (CIA) and analyzing the correlation of vulnerabilities between each node make it possible to calculate the attack priority. In the experiment, the risk scores of nodes and edges and the risk of each attack route were calculated. Moreover, the most threatening attack route was found by comparing the attack route risk. This confirmed that the proposed method calculated the risk of the network attack route and was able to effectively select the network route by providing the network route priority according to the risk score.
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