Department of Computer Science
Modeling and predicting the dynamics of mobile virus spread affected by human behavior
Viruses and malwares can spread from computer networks to mobile networks with the rapid growth of smart cellpone users. In a mobile network, viruses and malwares can cause privacy leakage, extra charges, remote listening and accessing private short messages and call history logs etc. Furthermore, they can jam wireless servers by sending thousands of spam messages or track user positions via GPS. Because of the potential damages of mobile viruses, it is important for us to design a realistic propagation model to observe and understand the propagation mechanisms of mobile viruses. In this paper, we propose a two-layer model to simulate the propagation process of BT-based and SMS-based viruses in mobile networks. Different from previous work, here we focus on the impacts of human behavior, i.e., human operations and mobility patterns, on virus propagation. Through simulations, we aim to gain some insights into how human behavior affects the dynamics of virus spread in mobile networks. © 2011 IEEE.
human behavior, mobile networks, virus spread dynamics
Source Publication Title
2011 IEEE International Symposium on a World of Wireless, Mobile, and Multimedia Networks
Link to Publisher's Edition
Gao, Chao, and Jiming Liu. "Modeling and predicting the dynamics of mobile virus spread affected by human behavior." 2011 IEEE International Symposium on a World of Wireless, Mobile, and Multimedia Networks (2011): 1-9.