Research on Network Security Quantitative Model Based on Probabilistic Attack Graph

Research on Network Security Quantitative Model Based on Probabilistic Attack Graph

In order to identify the threat of computer network security and evaluate its fragility comprehensively, the related factors of network security are studied, and the methods based on attack graph are improved. Based on the attribute attack graph, the probabilistic attack graph model is generated by...

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Bibliographic Details
Main Authors: Cui Yimin, Li Junmei, Zhao Wei, Luan Cheng
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:ITM Web of Conferences
Online Access:https://www.itm-conferences.org/articles/itmconf/pdf/2019/01/itmconf_amcse18_02003.pdf
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spelling doaj-ee94633a956d4fb59459ec43cad64de52021-02-02T08:15:14ZengEDP SciencesITM Web of Conferences2271-20972019-01-01240200310.1051/itmconf/20192402003itmconf_amcse18_02003Research on Network Security Quantitative Model Based on Probabilistic Attack GraphCui Yimin0Li Junmei1Zhao Wei2Luan Cheng3Beijing Institute of System EngineeringBeijing Institute of System EngineeringBeijing Institute of System EngineeringBeijing Institute of System EngineeringIn order to identify the threat of computer network security and evaluate its fragility comprehensively, the related factors of network security are studied, and the methods based on attack graph are improved. Based on the attribute attack graph, the probabilistic attack graph model is generated by adding various factors which affect network security. The model uses security equipment performance data, common vulnerability scoring system data and etc. to calculate priori probability, finally obtains the network security index, and carries on the exploratory analysis. The experimental results show that the model is feasible and effective. Compared with other vulnerability assessment methods, the model has the characteristics of comprehensive evaluation and concise calculation.https://www.itm-conferences.org/articles/itmconf/pdf/2019/01/itmconf_amcse18_02003.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Cui Yimin
Li Junmei
Zhao Wei
Luan Cheng
spellingShingle Cui Yimin
Li Junmei
Zhao Wei
Luan Cheng
Research on Network Security Quantitative Model Based on Probabilistic Attack Graph
ITM Web of Conferences
author_facet Cui Yimin
Li Junmei
Zhao Wei
Luan Cheng
author_sort Cui Yimin
title Research on Network Security Quantitative Model Based on Probabilistic Attack Graph
title_short Research on Network Security Quantitative Model Based on Probabilistic Attack Graph
title_full Research on Network Security Quantitative Model Based on Probabilistic Attack Graph
title_fullStr Research on Network Security Quantitative Model Based on Probabilistic Attack Graph
title_full_unstemmed Research on Network Security Quantitative Model Based on Probabilistic Attack Graph
title_sort research on network security quantitative model based on probabilistic attack graph
publisher EDP Sciences
series ITM Web of Conferences
issn 2271-2097
publishDate 2019-01-01
description In order to identify the threat of computer network security and evaluate its fragility comprehensively, the related factors of network security are studied, and the methods based on attack graph are improved. Based on the attribute attack graph, the probabilistic attack graph model is generated by adding various factors which affect network security. The model uses security equipment performance data, common vulnerability scoring system data and etc. to calculate priori probability, finally obtains the network security index, and carries on the exploratory analysis. The experimental results show that the model is feasible and effective. Compared with other vulnerability assessment methods, the model has the characteristics of comprehensive evaluation and concise calculation.
url https://www.itm-conferences.org/articles/itmconf/pdf/2019/01/itmconf_amcse18_02003.pdf
work_keys_str_mv AT cuiyimin researchonnetworksecurityquantitativemodelbasedonprobabilisticattackgraph
AT lijunmei researchonnetworksecurityquantitativemodelbasedonprobabilisticattackgraph
AT zhaowei researchonnetworksecurityquantitativemodelbasedonprobabilisticattackgraph
AT luancheng researchonnetworksecurityquantitativemodelbasedonprobabilisticattackgraph
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