Abstract
Power Grid as a kind of complex network is particularly important for every country, even brings huge losses if the power grid suffered from natural or even artificial attacks. Therefore, how to investigate the vulnerable edges of the power grid with under attacks has become an important proposition. In this paper, taking the US power grid as an example, by deliberately deleting some percent of edges according to different strategies which represents different attacks apparently, we calculate the collapse degree of the attacked network by three metrics (The largest connected component G, efficiency E, and average distance L). We found that, under intentional attack on the edges with higher betweenness centrality and the ones with larger multiplication of node betweenness centrality, the US power grid is inferior in invulnerability. The methods used in this paper could be used to identify the vulnerable edges of complex networks, especially for the key infrastructures.
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References
Arianos, S., Bompard, E., Carbone, A., et al.: Power grids vulnerability: a complex network approach. Chaos 19(1), 175 (2009)
Koç, Y., Warnier, M., Van Mieghem, P., et al.: The impact of the topology on cascading failures in electric power grids. Comput. Sci. (2013)
Kadloor, S., Santhi, N.: Understanding cascading failures in power grids. Comput. Sci. 28(5), 24–30 (2012)
Wang, X., Koc, Y., Robert, E., et al: A network approach for power grid robustness against cascading failures. In: 2015 7th International Workshop on Reliable Networks Design and Modeling (RNDM). IEEE (2015)
Simonsen, I., Buzna, L., Peters, K., et al.: Transient dynamics increasing network vulnerability to cascading failures. Phys. Rev. Lett. 100(21), 218701 (2008)
Buldyrev, S.V., Parshani, R., Paul, G., et al.: Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010)
Schaub, M.T., Lehmann, J., Yaliraki, S.N., et al.: Structure of complex networks: quantifying edge-to-edge relations by failure-induced flow redistribution. Netw. Sci. 2(01), 66–89 (2014)
Yong, Y., Yu, F.: Case study on survivability of urban rail transit network. Logistics Technol. 37(12), 58–62 (2018)
Sun, Y., Yang, D., Meng, L., et al.: Universal framework for vulnerability assessment of power grid based on complex networks. In: The 30th Chinese Control and Decision Conference (2018)
Runze, W., Wanxu, W., Li, L., Bing, F., Liangrui, T.: Topology diagnosis of power communication network based on node influence. Power Syst. Prot. Control 47(10), 147–155 (2019)
Riondato, M., Kornaropoulos, E.M.: Fast approximation of betweenness centrality through sampling. Data Min. Knowl. Discov. 30(2), 438–475 (2016). (S1384-5810)
Segarra, S., Ribeiro, A.: Stability and continuity of centrality measures in weighted graphs. IEEE Trans. Sig. Process. 64(3), 543–555 (2016)
Yun, L.: Node importance rank by attribute reduction set evaluation and application. Shandong Normal University (2018)
Li, S., Wu, X., Zhu, C., Li, A., Li, L., Jia, Y.: Vulnerability of complex networks under multiple node-based attacks. In: IET International Conference on Information & Communications Technologies (2013)
Ruan, Y., Lao, S.-Y., Wang, J., Bai, L., Chen, L.-D.: Node importance measurement based on neighborhood similarity in complex network. Acta Phys. Sin. 66(03), 371–379 (2017)
Li, C., Wei, L., Lu, T., Gao, W.: Invulnerability simulation analysis of compound traffic network in urban agglomeration. J. Syst. Simul. 30(02), 489–496 (2018)
Sun, K., Han, Z.X., Cao, Y.J.: Review on models of cascading failures in complex power grid. Power Syst. Technol. 13, 1–9 (2005)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440 (1998)
Yuejin, T., Xin, L., Jun, W., Hongzhong, D.: Main scientific problems for the invulnerability research of complex networks. In: The 15th Chinese Congress of Systems Science and Systems Engineering Proceeding. Systems Engineering Society of China (2008)
Verma, T., Ellens, W., Kooij, R.E.: Context-independent centrality measures underestimate the vulnerability of power grids. Int. J. Crit. Infrastruct. 11(1), 62 (2013)
Tian, Z., et al.: Real time lateral movement detection based on evidence reasoning network for edge computing environment. IEEE Trans. Ind. Inform. 15(7), 4285–4294 (2019)
Tian, Z., Su, S., Shi, W., Du, X., Guizani, M., Yu, X.: A data-driven method for future internet route decision modeling. Future Gener. Comput. Syst. 95, 212–220 (2019)
Li, S., Li, L., Yang, Y., Luo, Q.: Revealing the process of edge-based-attack cascading failures. Nonlinear Dyn. 69(3), 837–845 (2012)
Li, S., Li, L., Jia, Y., Liu, X., Yang, Y.: Identifying vulnerable nodes of complex networks in cascading failures induced by node-based attacks. Math. Probl. Eng. 2013, 938 (2013)
Zhao, D., Li, L., Peng, H., Luo, Q., Yang, Y.: Multiple routes transmitted epidemics on multiplex networks. Phys. Lett. A 378, 770–776 (2014)
Acknowledgement
This research was funded by NSFC (No. 61672020, U1803263, U1636215), (No.18-163-15-ZD-002-003-01), National Key Research and Development Program of China (No. 2019QY1406), Key R&D Program of Guangdong Province(No. 2019B010136003, 2019B010137004), A Project of Shandong Province Higher Educational Science and Technology Program (No. J16LN61), and the National Key research and Development Plan (No. 2018YFB1800701, No. 2018YFB0803504, and No. 2018YEB1004003).
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Li, Y., Li, S., Chen, Y., He, P., Wu, X., Han, W. (2019). Electric Power Grid Invulnerability Under Intentional Edge-Based Attacks. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_37
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DOI: https://doi.org/10.1007/978-981-15-1304-6_37
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