Abstract
Aiming at the problems of the network security evaluation indexes, which are one-sided and difficult to be strictly quantified, this paper proposes the multidimensional system security evaluation method based on AHP and grey relational analysis. Under the guidance of the construction principle of system security evaluation model, this paper puts the source of factors affecting network security as the criterion of dimension Division, and constructs a multidimensional system security evaluation model for environmental security, network security and vulnerability security. On this basis, this paper combines AHP and grey relational analysis theory, and evaluate system security comprehensively and quantitatively. The multidimensional system security evaluation method based on AHP and grey relational analysis can consider the relationship between qualitative and quantitative factors in system security, and it is highly logical and flexible. This method also can effectively solve the problem that system security is difficult to evaluate objectively and quantitatively, and the system security evaluation can be pushed from a simple rough comparison to a comprehensive quantitative calculation stage.
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References
China Internet Network Information Center. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201902/P020190318523029756345.pdf. Accessed 22 Sep 2019
Zhao, M.: Survey on technology of network security assessment. Comput. Sci. Appl. 05(1), 18–24 (2015)
Chen, J.: A network security risk assessment model based on unascertained mathematics. J. Air Force Eng. Univ. 15(2), 91–94 (2014)
Huang, X.: Research on network security evaluation system based on fuzzy comprehensive evaluation method. In: International Conference on Economics (2017)
Zhang, Y.: DS theory and hierarchical weight based network security risk assessment. Comput. Appl. Soft. 28(11), 294–297 (2011)
Liu, H.: Network security evaluation model based on uncertainty reasoning. J. Acad. Armored Force Eng. 6 (2006)
Yao, L., Dong, P., Zheng, T., et al.: Network security analyzing and modeling based on Petri net and Attack tree for SDN. In: International Conference on Computing. IEEE (2016)
Yin, X., Fang, Y., Liu, Y.: Real-time risk assessment of network security based on attack graphs, vol. 92, pp. 75–80 (2013)
Qi, Z., Zhou, C., Tian, Y.C., et al.: A fuzzy probability Bayesian network approach for dynamic cybersecurity risk assessment in industrial control systems. IEEE Trans. Ind. Inform. 99, 1 (2018)
Swarup, K.S.: Artificial neural network using pattern recognition for security assessment and analysis. Neurocomputing 71(4–6), 983–998 (2008)
Wang, C., Jing, Z., Li, X.: Research on DDoS attacks detection based on RDF-SVM. In: International Conference on Intelligent Computation Technology and Automation (2017)
Zhang, Y.B., Yan, Z.Q.: Researches on the network security evaluation method based on BP neural network. Appl. Mech. Mater. 686, 470–473 (2014)
Wang, C.Y.: Assessment of network security situation based on grey relational analysis and support vector machine. Appl. Res. Comput. 30(6), 1859–1862 (2013)
Yang, J., Chen, Q.B.: Network security evaluation based on grey relation projection multi-criteria decision. Comput. Knowl. Technol. 2011(29), 76 (2011)
Xiang, S., Lv, Y., Xia, C., Li, Y., Wang, Z.: A method of network security situation assessment based on hidden Markov model. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds.) ISICA 2015. CCIS, vol. 575, pp. 631–639. Springer, Singapore (2016). https://doi.org/10.1007/978-981-10-0356-1_65
Li, X., Xu, J., Li, D.: Index system of reliability evaluation for distribution network based on analytic hierarchy process. Proc. Chin. Soc. Univ. Electr. Power Syst. Autom. 21(3), 69–74 (2009)
Tian, G., Zhang, H., Zhou, M.C., et al.: AHP, gray correlation, and TOPSIS combined approach to green performance evaluation of design alternatives. IEEE Trans. Syst. Man Cybern. Syst. 99, 1–13 (2017)
CNNVD: Vulnerability information. http://www.cnnvd.org.cn/web/vulnerability/querylist.tag. Accessed 22 Sep 2019
rapid7user. https://sourceforge.net/projects/metasploitable/files/Metasploitable2/. Accessed 22 Sep 2019
Tenable. https://www.tenable.com/products/nessus-vulnerability-scanner. Accessed 22 Sep 2019
Ganglia: Ganglia Monitoring System. http://ganglia.info/?page_id=66. Accessed 22 Sep 2019
Ma, R., Ge, H., Gu, S.G., et al.: A method for determining the reference framework of network security metric index system. J. Cyber Secur. 4(1), 67–78 (2019)
Acknowledgement
This work was supported by National Key R&D Program of China (Grant No. 2016YFB0800700).
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Zhao, X., Xu, H., Wang, T., Jiang, X., Zhao, J. (2020). Research on Multidimensional System Security Assessment Based on AHP and Gray Correlation. In: Han, W., Zhu, L., Yan, F. (eds) Trusted Computing and Information Security. CTCIS 2019. Communications in Computer and Information Science, vol 1149. Springer, Singapore. https://doi.org/10.1007/978-981-15-3418-8_13
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DOI: https://doi.org/10.1007/978-981-15-3418-8_13
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