Fast response to infection spread and cyber attacks on large-scale networks

We present a strategy for designing fast and practical methods of response to cyber attacks and infection spread on complex weighted networks. In these networks, vertices 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 susceptible-infected-susceptible (SIS) epidemiological model. The objective is to detect the network vertices that have to be secured (or immunized) in order to keep a low level of infection in the system.