Identifying critical nodes in multi-layered networks under multi-vector malware attack

Abstract

Computer viruses are evolving by developing multiple spreading mechanisms that are simultaneously used during the infection process. The identification of the nodes that allow a better spreading efficiency of these kind of viruses is becoming a determinant part of the defensive strategy against malware. These multi-vector viruses can be modeled in multi-layered networks in which each node belongs simultaneously to different layers, adapting the spreading vector to the properties of the layer. This way, the same virus has different propagation rates in each layer and also in the multi-layered network considered as a whole. The set of nodes selected as initial group of infected subjects can determine the final propagation of the infection.Computer viruses are evolving by developing multiple spreading mechanisms that are simultaneously used during the infection process. The identification of the nodes that allow a better spreading efficiency of these kind of viruses is becoming a determinant part of the defensive strategy against malware. These multi-vector viruses can be modeled in multi-layered networks in which each node belongs simultaneously to different layers, adapting the spreading vector to the properties of the layer. This way, the same virus has different propagation rates in each layer and also in the multi-layered network considered as a whole. The set of nodes selected as initial group of infected subjects can determine the final propagation of the infection.