Source-linked AI summary
Understanding the spreading patterns of mobile phone viruses
P. Wang, M. Gonzalez, C. A. Hidalgo, A. -L. Barabasi
TL;DR
The paper models mobile-user mobility and call-graph structure to characterize mobile-virus spreading. It finds slow Bluetooth propagation, while MMS infections are constrained by a market-share phase transition.
Problem
Mobile-virus spreading patterns and the conditions enabling broad outbreaks require characterization as smartphone adoption and operating-system market shares increase.
Method
The study models user mobility, call-graph fragmentation, operating-system market share m, and latency time T(q,m).
Results
At market share m_c=0.095, call-graph structure undergoes a percolation phase transition; below it, MMS viruses reach only a small m-dependent fraction of users.
Takeaways & Limitations
Bluetooth viruses spread slowly because of human mobility, whereas MMS viruses could spread rapidly but are currently limited by call-graph fragmentation.
Takeaways & Limitations
The generating-function formalism introduces a small systematic deviation.
Abstract
from arXiv · showhide
We model the mobility of mobile phone users to study the fundamental spreading patterns characterizing a mobile virus outbreak. We find that while Bluetooth viruses can reach all susceptible handsets with time, they spread slowly due to human mobility, offering ample opportunities to deploy antiviral software. In contrast, viruses utilizing multimedia messaging services could infect all users in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating system's market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.