2020
DOI: 10.1109/access.2020.3015551
|View full text |Cite
|
Sign up to set email alerts
|

A Vulnerability Risk Assessment Method Based on Heterogeneous Information Network

Abstract: 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. Ad… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2

Citation Types

0
4
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
4
3
1

Relationship

1
7

Authors

Journals

citations
Cited by 12 publications
(4 citation statements)
references
References 29 publications
0
4
0
Order By: Relevance
“…A software vulnerability rating method, SVRA, was proposed, which uses a vulnerability database to analyze the frequency of CVSS metrics at diferent times, and then gives equations for exploitability and impact scores based on these frequencies. Wang et al [33] considered that CVSS metrics ignore the impact of vulnerabilities on specifc networks, i.e., the same vulnerabilities that exist in diferent network environments are assigned duplicate values, and the attack graph still sufers from scalability and readability issues. To address the above issues, the authors innovatively propose a vulnerability risk assessment method based on heterogeneous information networks.…”
Section: Related Workmentioning
confidence: 99%
“…A software vulnerability rating method, SVRA, was proposed, which uses a vulnerability database to analyze the frequency of CVSS metrics at diferent times, and then gives equations for exploitability and impact scores based on these frequencies. Wang et al [33] considered that CVSS metrics ignore the impact of vulnerabilities on specifc networks, i.e., the same vulnerabilities that exist in diferent network environments are assigned duplicate values, and the attack graph still sufers from scalability and readability issues. To address the above issues, the authors innovatively propose a vulnerability risk assessment method based on heterogeneous information networks.…”
Section: Related Workmentioning
confidence: 99%
“…Wang., et al, [4] proposed a ranking method based on the heterogeneous information network 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 and the authors compare the proposed method with CVSS and attack graph-based methods.…”
Section: Related Workmentioning
confidence: 99%
“…To enhance the model for detecting and preventing the various attacks in the heterogeneous web application since the tools used earlier will not ensure prevention mechanisms to mitigate detected vulnerabilities and attacks. The objective is also to incorporate suitable machine learning techniques into the model for accurate and effective prediction and forecasting of attacks with their root causes, to analyze the impact of attack penetration level from web application to web services and to mitigate the percentage of vulnerabilities and attacks by recommending preventive measures and best practices [4]. Due to the diversity in the detection techniques, there is a need for a standard model for detecting all possible vulnerabilities.…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, Jasna Markovic-Petrovic, Mirjana Stojanovic and Slavica Bostjancic Rakas proposed a new method for security risk assessment in supervisory control and data acquisition (SCADA) networks using fuzzy logic [5]. Wenrui Wang, Fan Shi, Min Zhang, Chengxi Xu and Jinghua Zheng proposed a heterogeneous information network based ranking method for vulnerability risk assessment in a particular network [6]. Jiali Wang, Martin Neil and Norman Fenton obtained a combined Extended Factor Analysis of Information Risk-Bayesian Networks (EFBN) approach using Monte Carlo simulation and showed that it can provide an integrated solution for cybersecurity risk assessment and decision making [7].…”
Section: Introductionmentioning
confidence: 99%