  Most communication networks are complex. In this paper, we address one of the
fundamental problems we are facing nowadays, namely, how we can efficiently
protect these networks. To this end, we study an immunization strategy and
found that it works as good as targeted immunization, but using only local
information about the network topology. Our findings are supported with
numerical simulations of the Susceptible-Infected-Removed (SIR) model on top of
real communication networks, where immune nodes are previously identified by a
covering algorithm. The results provide useful hints in the way to design and
deploying a digital immune system.
