Stochastic modeling of computer virus spreading with warning signals

Modeling and understanding virus spreading is a crucial issue in computer security. Epidemiological models have been proposed to deal with this problem. We investigate the dynamics of computer virus spreading by considering an stochastic susceptible-infected-removed-susceptible (SIRS) model where immune computers send warning signals to reduce the propagation of the virus among the rest of the computers in the network. We perform an exhaustive analysis of the main indicators of the spread and persistence of the infection. To this end, we provide a detailed study of the quasi-stationary distribution, the number of cases of infection, the extinction time and the hazard time.