It’s not just the flu that thrives aboard a busy flight or within a hectic workplace. Computer worms could spread in remarkably similar fashion, according to a new mathematical model.
Several proof-of-concept worms have been created and two, Cabir and Commwarrior, successfully spread in the “wild” although not very efficiently.
Nonetheless, as portable devices become more fully functional, the risk of a full-blown outbreak is only likely to increase, which makes modelling an outbreak important to devising countermeasures.
Christopher Rhodes, an expert on infectious diseases at Imperial College London and Maziar Nekovee, a researcher at BT’s research lab in Suffolk, UK, created a mathematical model to better understand the way a wireless computer worm would spread between portable devices.
In December 2007, another researcher, Steven Myers, at Indiana University, US, developed a model to show how a wireless computer worm might spread between stationary Wi-Fi routers.
The new model adds another dimension by factoring in the movement of people carrying infected or vulnerable devices.
Rhodes and Nekovee’s model considers a crowd of people carrying Bluetooth-enabled smartphones, each with a fixed range for connecting to other phones in the crowd.
Members of the crowd move in a straight line, and at a fixed speed. If a phone is infected with a worm it then has a fixed probability of infecting other devices while they are within range.
The work shows that the spread of a wireless worm can be represented using a common tool for representing virus outbreaks, called a standard mass-action mixing model. “The transmission model is actually very similar to something like influenza,” Rhodes told New Scientist.
This means, just like a real virus, a wireless worm would spread most efficiently in a busy setting and could also hop between geographically distant locations, for example aboard a plane.
“A Bluetooth worm’s ability to spread is rooted in person-to-person contact,” says Eric Chien, a chief researcher at Symantec Security Response in the US. So a mass-action mixing model provides a good approximation.
“Knowledge that person-to-person contact, or rather device to device contact, represents a major factor in how a Bluetooth worm spreads is definitely important,” Chien adds.
He also suggests that a simple mitigation strategy would be to disable non-essential Bluetooth communications during an outbreak: “This reduces the contact occurrences and would be analogous to wearing a surgical mask in areas of potential infection.”
Bruce Schneier of security company BT Counterpane describes the work as “great and interesting reserach.”
“What’s interesting is that malware depends a lot on the characteristics of the underlying network,” he says. “The phone network is different [to existing networks] and the spreading characteristics will be different.”
However, he doubts whether it will lead to any radically new strategies for defending against such threats. “People subscribe to automatic update, because worms spread faster,” he says. “Fast spreading is a characteristic of wireless worms, too.”