  We present a strategy for designing fast methods of response to cyber attacks
and infection spread on complex weighted networks. In these networks, nodes can
be interpreted as primitive elements of the system, and weighted edges reflect
the strength of interaction among these elements. The proposed strategy belongs
to the family of multiscale methods whose goal is to approximate the system at
multiple scales of coarseness and to obtain a solution of microscopic scale by
combining the information from coarse scales. In recent years these methods
have demonstrated their potential for solving optimization and analysis
problems on large-scale networks. We consider an optimization problem that is
based on the SIS epidemiological model. The objective is to detect the network
nodes that have to be immunized in order to keep a low level of infection in
the system.
