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Spreading Patterns of Mobile Phone Viruses

Center for Complex Network Research, Northeastern University

Publications

Understanding the spreading patterns of mobile phones viruses, P. Wang, M.C. González, C.A. Hidalgo and A.-L.Barabási, Science 324, 1071-1076 (2009).

Media

Science, Nature Physics, NSF, BBC, Scientific American, PhysOrg, ND, NEU

Background Materials
Mobile viruses are little more than a nuisance today, but given our increased reliance on wireless communication, in the near future they could pose more risk than their PC based counterparts. Despite of the more than three hundred mobile viruses known so far, little is known about their spreading pattern, partly due to a lack of data on the communication and travel patterns of mobile phone users. Starting from the traffic and the communication pattern of six million mobile phone users, we model the vulnerability of mobile communications against potential virus outbreaks...

Good introduction

An overview of mobile device security,

Malware Goes Mobile

The spread of mobile viruses is aided by two dominant communication protocols. First, a Bluetooth virus can infect Bluetooth-activated phones within a distance from 10 to 30m. Second, an MMS virus can send a copy of itself to all mobile phones whose numbers are found in the infected phone’s address book.

Mobility Patterns

Mobility data

 

The cell phone dataset records provide the location of each user during each call. Yet, the sampling is often too sparse. To identify the hourly location we developed the following procedure: we break each day into 24 hour long time intervals. If the user calls during a specific hour period, we set user’s position to the tower indicated by the dataset.
Mobility's tempal and spatial patterns  

Given the sparseness of the calls, this leaves us with an incomplete location record. Therefore, we developed a methodology to identify the user’s likely location building on the results of human mobility patterns.

We generate its location as following:

(1) Decide if the user moves.

(2) Extract a position seed.

(3) Scaling and rotating user’s trajectory.

(4) Check if new position is in the country.

(5) Find the nearest tower.

Methodology test

We test our methodology by comparing the statistical properties of the simulated trajectories and those observed for the empirical data. In general, we find that our simulation does not introduce considerable biases in the statistical properties of the observed trajectories. Please see SOM for detail.

Spreading Patterns

Bluethooh and MMS viruses' spreading patterns

 

The spread of mobile viruses is aided by two dominant communication protocols. First, a Bluetooth virus can infect Bluetooth-activated phones within a distance from 10 to 30m. Second, an MMS virus can send a copy of itself to all mobile phones whose numbers are found in the infected phone’s address book.
Why no large-scale epidemic now, when there is?  

The current lack of major mobile virus outbreak can not be attributed to the absence of effective mobile viruses, but it is mainly rooted in the fragmentation of the call graph. Given, however, the rapid growth in the number of smartphones and the increasing market share of a few OS, it is not unconcievable that the phase transition point will be reached in the near future, raising the possibility of major viral outbreaks.
The significance of our research comes in its ability to explain why we have not observed a significant MMS outbreak so far: currently the market share of the largest OS is less than m~0.03, well under the predicted percolation transition point mc~0.095. This, naturally, represents only an approximation. For example, if we increase the observational period from a few days to three months, mc decreases to mc=0.051. The question is, what the real value of mc, and how does it compare to the market share of the largest OS?
Spatial Spreading Patterns  
Bluetooth and MMS viruses differ in their spatial spreading patterns: a Bluetooth virus follows a wave like pattern, infecting predominantly users in the vicinity of the virus’s release point, while an MMS virus follows a more delocalized pattern, given that the users’ address book often contains phone numbers of far away users. We also made additional simulation to compare the spatial spreading pattern of a hybrid virus to the spreading pattern defined by Bluetooth and MMS viruses confirming that the spatial spreading pattern defined by hybrid viruses represents a combination of the spreading patterns defined by Bluetooth and MMS viruses.
Movies    

BLUETOOTH VIRUS

MMS VIRUS

SPREAD METHODS

Virus Infection Movies

http://www.youtube.com/watch?v=3agxFyl0SeI

http://www.youtube.com/watch?v=ZDlGhdp4DY&feature=related