Abstract
Combining the spread velocity, the epidemic threshold and the infection scale at steady state, a new network robust measure with respect to the virus attacks is proposed in this paper. Through examples, we show that spread velocity plays an important role on the network robustness. By using the SI and SIS epidemic model, we analyze the robustness of homogeneous networks. The results show that the irregularity in node degrees decreases the robustness of the networks. Moreover, the simulation results show that the network becomes more fragile as the average degree grows in both homogeneous and heterogeneous networks.
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Song, B., Jing, Z., Jay Guo, Y., Liu, R.P., Zhou, Q. (2020). A Novel Measure to Quantify the Robustness of Social Network Under the Virus Attacks. In: Xiang, Y., Liu, Z., Li, J. (eds) Security and Privacy in Social Networks and Big Data. SocialSec 2020. Communications in Computer and Information Science, vol 1298. Springer, Singapore. https://doi.org/10.1007/978-981-15-9031-3_17
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DOI: https://doi.org/10.1007/978-981-15-9031-3_17
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