  We study the response of complex networks subject to attacks on vertices and
edges. Several existing complex network models as well as real-world networks
of scientific collaborations and Internet traffic are numerically investigated,
and the network performance is quantitatively measured by the average inverse
geodesic length and the size of the largest connected subgraph. For each case
of attacks on vertices and edges, four different attacking strategies are used:
removals by the descending order of the degree and the betweenness centrality,
calculated for either the initial network or the current network during the
removal procedure. It is found that the removals by the recalculated degrees
and betweenness centralities are often more harmful than the attack strategies
based on the initial network, suggesting that the network structure changes as
important vertices or edges are removed. Furthermore, the correlation between
the betweenness centrality and the degree in complex networks is studied.
