Vulnerability of state-interdependent networks under malware spreading

• A propagation model of modern malware using several vectors of infection is studied.
• We use SI dynamics on multilayer networks with the same state of nodes across layers.
• We develop a formalism to analytically deal with this model as in a single network.
• We use as case study the network of scientific collaborations/author affiliations.
• We find that the topology of this network makes it very vulnerable to modern malware.

Computer viruses are evolving by developing spreading mechanisms based on the use of multiple vectors of propagation. The use of the social network as an extra vector of attack to penetrate the security measures in IP networks is improving the effectiveness of malware, and have therefore been used by the most aggressive viruses, like Conficker and Stuxnet. In this work we use interdependent networks to model the propagation of these kind of viruses. In particular, we study the propagation of a SIS model on interdependent networks where the state of each node is layer-independent and the dynamics in each network follows either a contact process or a reactive process, with different propagation rates. We apply this study to the case of existing interdependent networks, namely a Spanish scientific community of Statistical Physics, formed by a social network of scientific collaborations and a physical network of connected computers in each institution. We show that the interplay between layers increases dramatically the infectivity of viruses in the long term and their robustness against immunization.