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Network Risk Assessment Method Based on Asset Correlation Graph

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Trusted Computing and Information Security (CTCIS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 960))

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Abstract

In order to enhance the security of network operations, establish effective security measures, prevent the destruction of security incidents, and reduce or eliminate the losses caused by threats through network risk assessment is of important practical significance. However, most risk assessment methods focus on the research of threats and vulnerabilities. There are relatively few researches on risk based on network assets and there is a lack of accuracy in risk assessment. Therefore, this paper proposes a network risk assessment method based on asset association graphs. The method first describes the network from the perspective of asset interconnection and builds an asset association graph; secondly, it builds a threat scenario based on the asset association graph, identifies a threat event, and uses the probability of a threat event and the loss caused by the asset to obtain a quantitative description of the risk assessment; Different network risk levels and make decisions. Experiments show that the method of network risk assessment based on asset association proposed in this paper can realize the risk assessment of all assets, hosts and entire network system in the network, and provide effective guidance for network security protection.

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Acknowledgments

This article is supported by National Key R&D Program of China (Grant no. 2016YFB0800700) and National Natural Science Foundation of China (Grant no. U1636115).

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Correspondence to Chun Shan .

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Shan, C., Gao, J., Hu, C., Guan, F., Zhao, X. (2019). Network Risk Assessment Method Based on Asset Correlation Graph. In: Zhang, H., Zhao, B., Yan, F. (eds) Trusted Computing and Information Security. CTCIS 2018. Communications in Computer and Information Science, vol 960. Springer, Singapore. https://doi.org/10.1007/978-981-13-5913-2_5

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  • DOI: https://doi.org/10.1007/978-981-13-5913-2_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5912-5

  • Online ISBN: 978-981-13-5913-2

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