Agent-Based Model to Study and Quantify the Evolution Dynamics of Android Malware Infection

In the last years the number of malware Apps that the users download to their devices has risen. In this paper, we propose an agent-based model to quantify the Android malware infection evolution, modeling the behavior of the users and the different markets where the users may download Apps. The model predicts the number of infected smartphones depending on the type of malware. Additionally, we will estimate the cost that the users should afford when the malware is in their devices. We will be able to analyze which part is more critical: the users, giving indiscriminate permissions to the Apps or not protecting their devices with antivirus software, or the Android platform, due to the vulnerabilities of the Android devices that permit their rooted. We focus on the community of Valencia, Spain, although the obtained results can be extrapolated to other places where the number of Android smartphones remains fairly stable.