Abstract
The intelligence of power grids has made the relationship between distribution networks and the Internet more and more compact. Therefore, in order to cope with the various threats in the situation of smart grid, it is necessary to study from multiple perspectives. Among them, attack scenario reconstruction is a more effective method of network security defense. However, the existing attack scenario reconstruction technology is not combined with the actual situation of the power grid. In this paper, we proposed a grid-based attack scenario reconstruction framework which is based on big data. The framework consists of KNN-based attack data classification and state machine-based attack scenario restoration. In addition, we also implemented prototypes and evaluated the effectiveness and availability of databases provided by IDS in China Grid Corporation. The results show that the framework proposed in this paper improves the efficiency and accuracy of analyzing attacker strategies.
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Acknowledgements
The work is supported by State Grid Corporation of China Science and Technology Project: Research on Unknown Security Threat Detection Technology Based on Big Data Analysis (No. SGJSXT00JFJS1700101).
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Guo, L., Jin, Q., Liu, Y., Xia, Y., Hu, H. (2020). Big Data-Based Attack Scenario Reconstruction Architecture in Smart Grid. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_141
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DOI: https://doi.org/10.1007/978-981-13-6508-9_141
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