Reasoning about mobile malware using high performance computing based population scale models

We present a high performance computing (HPC) based modeling approach to reason about mobile malware. The ubiquity of smart phones and devices and the use of local protocols for disseminating information over such devices has raised new security challenges. The HPC approach to study mobile malware propagation problem involves: (i) a realistic and detailed representation of mobile devices, their time varying location, their usage patterns and the urban environment within which they are operated, leading to dynamic interaction networks over which malware can spread - these networks are large, heterogeneous and time varying; and (ii) a high performance computing based simulation environment that can study diffusion of malware over such networks. We use EpiCure, an individual based high performance simulation tool for malware modeling, that scales to networks spanning urban regions with over 10M individuals. We find that malware dynamics in realistic networks are very different from those in random waypoint (RWP) mobility models. Next, we study the impact of some of the worm model parameters and properties associated with population mobility and social contact networks; we use detailed statistical analysis to identify the significant parameters and their interaction. Finally, we use EpiCure to study SMS/MMS based malware and hybrid malware that spread using both proximity based Bluetooth networks and infrastructure based cellular networks.