Modeling of Malware Propagation in Wireless Mobile Networks with Hotspots Considering the Movement of Mobile Clients Based on Cosine Similarity

In this paper, we propose a deterministic epidemic model for malware propagation in wireless mobile environments, taking into account the presence of hotspots. Conventional epidemic models for wireless mobile environments typically assume that mobile hosts randomly move in a given area. However, in real-world scenarios, hotspots such as restaurants and universities often attract large gatherings of people. Therefore, the assumption of purely random movement is not suitable for modeling these scenarios. To realistically represent the movement patterns of mobile hosts, we incorporate the influence of hotspots into our model. Specifically, we formulate a system of Ordinary Differential Equations (ODEs) that captures the infection dynamics in scenarios where one or more hotspots affect host mobility. Our model introduces non-uniform movement probabilities based on cosine similarity, allowing us to reflect the tendency of mobile hosts to cluster around specific locations. By applying these movement probabilities to the ODEs, our epidemic model provides a more accurate representation of malware spreading behavior in hotspot-affected environments. We investigate how malware propagates through mobile hosts and compare the dynamics between the conventional and our proposed models. Numerical experiments demonstrate that our epidemic model effectively captures malware spreading behavior in mobile scenarios with hotspots.