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Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Doi
Abstract
In this paper, we explore the relationship between the topological characteristics of a
complex network and its robustness to sustained targeted attacks. Using synthesised
scale-free, small-world and random networks, we look at a number of network measures,
including assortativity, modularity, average path length, clustering coefficient, rich club
profiles and scale-free exponent (where applicable) of a network, and how each of these
influence the robustness of a network under targeted attacks. We use an established robustness
coefficient to measure topological robustness, and consider sustained targeted
attacks by order of node degree. With respect to scale-free networks, we show that assortativity,
modularity and average path length have a positive correlation with network
robustness, whereas clustering coefficient has a negative correlation. We did not find any
correlation between scale-free exponent and robustness, or rich-club profiles and robustness.
The robustness of small-world networks on the other hand, show substantial positive
correlations with assortativity, modularity, clustering coefficient and average path
length. In comparison, the robustness of Erdos-Renyi random networks did not have any
significant correlation with any of the network properties considered. A significant observation
is that high clustering decreases topological robustness in scale-free networks,
yet it increases topological robustness in small-world networks. Our results highlight the
importance of topological characteristics in influencing network robustness, and illustrate
design strategies network designers can use to increase the robustness of scale-free and
small-world networks under sustained targeted attacks
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