Modeling and validation of SMS worm propagation over social networks

Smartphones are getting more and more popular. SMS worms propagate themselves by sending messages, which can quickly infect millions of mobile phones and do great damage to users. Thus it is urgent to analyze and predict the propagation of SMS worms to lessen their potential threat. However, most existing models generate the similar smooth exponential curves which cannot accurately characterize the propagation of real world SMS worms. In this paper, we propose a novel model, SAIDR, based on the social network. In order to more accurately portray the real behaviors of mobile users, SAIDR first introduces two new states, the affected state and the dormant state. Furthermore, SAIDR takes three critical factors into account: the behaviors of users' checking newly arrived messages, the asymmetrical trust relationships between mobile users and the security consciousness of users. Moreover, comprehensive experiments have been done to evaluate the SAIDR model. Compared with the real world worm and the existing models, our model is more reasonable and thus can describe and predict the propagation dynamic of SMS worms better.