The past decades have seen a tremendous increase in mobile data traffic. Device-to-device (D2D) communication systems show great potential to complement existing cellular networks, however, direct communication adds the security risk of proximity-based malware propagation. This doctoral thesis focuses on the connectivity properties of dynamic D2D networks and the analysis of malware spread in the case of an infection. We define a realistic transmission mechanism for the malware and use chase-escape dynamics as a possible countermeasure. In this context, infection spreads via proximity-based interaction to susceptible neighbors. However, the infection will be purged if it tries to infect a "white knight" that carries the countermeasure, and the infected device will, in turn, become a white knight. We rigorously analyze the conditions under which percolation—i.e., infinite spread of malware across the spatial-geometric network—is possible and supplement our findings with simulation studies. The infection process is studied on the Random Geometic Graph and on a spatial geometric network, where the devices are distributed on Manhattan- or Poisson--Voronoi-based street systems.
Alexander Hinsen (Thu,) studied this question.