  We investigated the efficiency of attack strategies to network nodes when
targeting several complex model and real-world networks. We tested 5 attack
strategies, 3 of which were introduced in this work for the first time, to
attack 3 model (Erdos and Renyi, Barabasi and Albert preferential attachment
network, and scale-free network configuration models) and 3 real networks
(Gnutella peer-to-peer network, email network of the University of Rovira i
Virgili, and immunoglobulin interaction network). Nodes were removed
sequentially according to the importance criterion defined by the attack
strategy. We used the size of the largest connected component (LCC) as a
measure of network damage. We found that the efficiency of attack strategies
(fraction of nodes to be deleted for a given reduction of LCC size) depends on
the topology of the network, although attacks based on the number of
connections of a node and betweenness centrality were often the most efficient
strategies. Sequential deletion of nodes in decreasing order of betweenness
centrality was the most efficient attack strategy when targeting real-world
networks. In particular for networks with power-law degree distribution, we
observed that most efficient strategy change during the sequential removal of
nodes.
