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2016 ; 11
(9
): e0162289
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Attack Vulnerability of Network Controllability
#MMPMID27588941
Lu ZM
; Li XF
PLoS One
2016[]; 11
(9
): e0162289
PMID27588941
show ga
Controllability of complex networks has attracted much attention, and
understanding the robustness of network controllability against potential attacks
and failures is of practical significance. In this paper, we systematically
investigate the attack vulnerability of network controllability for the canonical
model networks as well as the real-world networks subject to attacks on nodes and
edges. The attack strategies are selected based on degree and betweenness
centralities calculated for either the initial network or the current network
during the removal, among which random failure is as a comparison. It is found
that the node-based strategies are often more harmful to the network
controllability than the edge-based ones, and so are the recalculated strategies
than their counterparts. The Barabási-Albert scale-free model, which has a highly
biased structure, proves to be the most vulnerable of the tested model networks.
In contrast, the Erd?s-Rényi random model, which lacks structural bias, exhibits
much better robustness to both node-based and edge-based attacks. We also survey
the control robustness of 25 real-world networks, and the numerical results show
that most real networks are control robust to random node failures, which has not
been observed in the model networks. And the recalculated betweenness-based
strategy is the most efficient way to harm the controllability of real-world
networks. Besides, we find that the edge degree is not a good quantity to measure
the importance of an edge in terms of network controllability.
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