Worm Propagation Modeling Considering Smartphones Heterogeneity and People Mobility

Abstract

Abstract-In recent years, the worldwide market for smartphones has grown dramatically. The kind of information stored in these devices makes them an attractive target for malware writers. Consequently, modeling of worm propagation in smartphones in order to predict the side effects of a new threat and understand the complex behavior of the modeled malware has received significant attention. One of the possible mechanisms for malware spreading are Bluetooth antennas, where the malware infects devices in its proximity as biological viruses do. Due to this strong similarity in the behaviors of self-replicating and propagation between mobile malware and biological viruses, most investigations of malware propagation in smartphones focus predominately on modeling its propagation dynamics by employing the classical epidemic theories in epidemiology. Cellular Automata (CA) models have emerged recently as a promising alternative to characterize worm propagation and understand its behavior. However, in the most of the existing CA models for mobile malware, it is assumed that all smartphones are homogeneous and that transmission time of the worm is one time cycle. In this work, a mathematical model to study the spatio-temporal propagation dynamics of Bluetooth worms based on CA and the compartmental epidemiological models is introduced. The model considers the local interactions between the smartphones and is able to simulate the individual dynamic of each device and the effect of mobility of their users on the infection propagation.