0000000001103609
AUTHOR
Juan Alegre-sanahuja
Agent-Based Model to Study and Quantify the Evolution Dynamics of Android Malware Infection
[EN] In the last years the number of malware Apps that the users download to their devices has risen. In this paper, we propose an agentbased 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 v…
Predicting mobile apps spread: An epidemiological random network modeling approach
[EN] The mobile applications business is a really big market, growing constantly. In app marketing, a key issue is to predict future app installations. The influence of the peers seems to be very relevant when downloading apps. Therefore, the study of the evolution of mobile apps spread may be approached using a proper network model that considers the influence of peers. Influence of peers and other social contagions have been successfully described using models of epidemiological type. Hence, in this paper we propose an epidemiological random network model with realistic parameters to predict the evolution of downloads of apps. With this model, we are able to predict the behavior of an app…