Abstract
Robustness measures the toleration of complex networks against random failures and malicious attacks. A malicious attack removes the most important node iteratively and destroys the network quickly. It is crucial to strengthen the network robustness against malicious attacks. In this paper, we propose an algorithm to strengthen the robustness with reduced change of network structure compared to state-of-the-art algorithms. The algorithm is called targeted variable neighborhood search (TVNS) algorithm. Experiments on real-world and random networks show that TVNS is efficient on strengthening the robustness against malicious attacks. The strengthened network against high degree adaptive attack shows an onion-like structure where nodes prefer to connect with similar degree nodes; while for the strengthened network against high betweenness adaptive attack, nodes prefer to connect with similar betweenness nodes.
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Acknowledgements
This study is supported by the National Natural Science Foundation of China (Grants No. 61861136005 and No. 61851110763).
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Rong, Q., Zhang, J., Sun, X., Wandelt, S. (2020). Network Strengthening Against Malicious Attacks. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 881. Springer, Cham. https://doi.org/10.1007/978-3-030-36687-2_63
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DOI: https://doi.org/10.1007/978-3-030-36687-2_63
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