A Novel Stochastic Approach for Modeling Random Scanning Worms

Scanning worms grow with different local velocities in different areas, because of non-uniformities that are present in real networks. The present work introduces a new stochastic model elaborating the classical epidemiological model for random scanning strategies. More specifically, random effects in worm spreading velocity are modeled by means of a stochastic differential equation where an explicit expression quantifying randomness is proposed. Furthermore, we explore whether deterministic or stochastic models are appropriate in order to describe the worm propagation phenomenon. To this end we introduce the scale of observation as a crucial parameter. Simulation results are presented validating the proposed analytical results.