Department of Computer Science
Modeling and restraining mobile virus propagation
Viruses and malwares can spread from computer networks into mobile networks with the rapid growth of smart cellphone users. In a mobile network, viruses and malwares can cause privacy data leakage, extra charges, and remote listening. Furthermore, they can jam wireless servers by sending thousands of spam messages or track user positions through GPS. Because of the potential damages of mobile viruses, it is important for us to gain a deep understanding of the propagation mechanisms of mobile viruses. In this paper, we propose a two-layer network model for simulating virus propagation through both Bluetooth and SMS. Different from previous work, our work addresses the impacts of human behaviors, i.e., operational behavior and mobile behavior, on virus propagation. Our simulation results provide further insights into the determining factors of virus propagation in mobile networks. Moreover, we examine two strategies for restraining mobile virus propagation, i.e., preimmunization and adaptive dissemination strategies drawing on the methodology of autonomy-oriented computing (AOC). The experimental results show that our strategies can effectively protect large-scale and/or highly dynamic mobile networks. © 2002-2012 IEEE.
adaptive dissemination, autonomy-oriented computing, human mobility, Mobile networks, phone virus, preimmunization
Source Publication Title
IEEE Transactions on Mobile Computing
Institute of Electrical and Electronics Engineers
Link to Publisher's Edition
Gao, Chao, and Jiming Liu. "Modeling and restraining mobile virus propagation." IEEE Transactions on Mobile Computing 12.3 (2013): 529-541.