Network resilience against intelligent attacks constrained by the degree-dependent node removal
Alessia Annibale, Anthony (Ton) C C Coolen and Ginestra Bianconi
Journal of Physics A: Mathematical and Theoretical
We study the resilience of
complex networks against attacks in which nodes
are targeted intelligently, but where
disabling a node has a cost to the attacker which depends on its degree. Attackers have
to meet these costs with limited resources, which constrains their actions.
A network's integrity is quantified in terms of the efficacy of the process that it supports.
We calculate how the optimal attack strategy and the most attack-resistant network degree statistics
depend on the node removal cost function and the attack resources.
The resilience of networks against intelligent attacks is found to depend strongly on the
node removal cost function faced by the attacker.
In particular, if node removal costs increase sufficiently fast
with the node degree, power law networks are found to be more resilient than
Poissonian ones, even against optimised intelligent attacks.