Abstract
With the development of power monitoring system, the continuous occurrence of network attacks has made people deeply aware of the importance of the power monitoring system network security. How to understand and evaluate the security of the network has become the focus of the power monitoring system network. In response to this problem, this article proposes a vulnerability assessment method. The purpose is to find out the hidden security risks in the network system and the path that may be invaded by the intruder, so that the problem can be found before the attack occurs. Subsequent to make up for the problems found to improve the security of the network system, this article is based on the attack graph and Bayesian network to realize the vulnerability assessment of the power monitoring system network, through the complex network to find the vulnerabilities in the network system can be from the network topology From the structural point of view, the attack graph is constructed from the network topology through the attack graph generation algorithm to determine the vulnerability and reachability of each node, and to correspond to the Bayesian network. The method is based on the Bayesian network. The network conducts an overall assessment. Experimental analysis shows that the vulnerability assessment method in this paper can effectively reflect the overall vulnerability of the power monitoring system network.
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References
Huang, J.: Analysis of industrial control network security. Netw. Secur. Inf. Technol. 03, 53–62 (2021)
Wang, H., Song, L., Peng, Z.: Evaluation and analysis of security vulnerability of autonomous network systems. Netw. Secur. Inf. Technol. 12, 128–132 (2020)
Chen, Z., Xie, N., Wang, C., Qian, Z.: Research on vulnerability assessment and robustness improvement strategy of complex power network based on fractal mechanism. Power Syst. Technol. 45(02), 657–665 (2021)
Zhao, X., Xu, H., Xue, J., Song, T., Hu, J., Yan, H.: Research on the method of discovering vulnerability in network system based on complex network. J. Inf. Secur. 4(01), 39–52 (2019)
Wang, H., Xiang, W.: The vulnerability of computer network topology and quantitative assessment methods. Autom. Instrum. 07, 63–64 (2017)
Tan, Y., Zhang, J., Li, X.: Importance evaluation of power grid nodes based on complex network theory. Comput. Eng. 45(11), 281–286 (2019)
Chen, Z., Xie, N., Wang, C., et al.: Research on vulnerability assessment and robustness improvement strategy of complex power network based on fractal mechanism. Power Syst. Technol. 45(02), 657–665 (2021)
Duan, J., Zheng, H.: Complex network vulnerability analysis method based on node importance. Control. Eng. 27(04), 692–696 (2020)
Ma, W.: Research on network vulnerability assessment based on attack graph and security metrics. J. Phys. Conf. Ser. 1774 (1), 3–5 (2021)
Wang, S.: Prediction and analysis of systemic network security model based on data mining. J. Northeast. Electric Power Univ. 39(06), 91–93 (2019)
Nie, H., Liu, L.: Fast power flow transferring based on bidirectional adjacent path and multi-branch disconnection. J. Northeast. Electric Power Univ. 39(01), 1–8 (2019)
Acknowledgements
This work is supported by the science and technology projectof State Grid Corporation of China “Research on Vulnerability Analysis and Threat Detection Key Technology of Power Monitoring System in Cyberspace” (Grand No.5108-202117055A-0-0-00).
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Qian, K., Jin, M., Zhang, D., Xiao, F., Zhang, P. (2022). Research on Evaluation Method of Network Vulnerability in Power Monitoring System. In: Pan, JS., Meng, Z., Li, J., Virvou, M. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 278. Springer, Singapore. https://doi.org/10.1007/978-981-19-1053-1_11
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DOI: https://doi.org/10.1007/978-981-19-1053-1_11
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