Digital ants protect critical infrastructure
deploy thousands of different types of digital ants, each looking for evidence of a threat,” Fulp said. “As they move about the network, they leave digital trails modeled after the scent trails ants in nature use to guide other ants. Each time a digital ant identifies some evidence, it is programmed to leave behind a stronger scent. Stronger scent trails attract more ants, producing the swarm that marks a potential computer infection.”
The concept has proven successful in testing on a small scale, but will it still work when it’s scaled up to protect something as large and complex as the nation’s power grid? Fulp and two of his students — computer science graduate students Michael Crouse and Jacob White — are working this summer with scientists at PNNL and from the University of California at Davis to answer that question. Even using PNNL’s vast computer platforms, they can only rely on computer simulations to predict the ants’ “behavior” up to a point.
This is where Associate Professor of Mathematics Ken Berenhaut, an expert in mathematical modeling and simulation, comes in. Berenhaut, along with graduate student Ross Hilton, will use modeling to help determine what will happen as the ants move about the smart grid from the hot water heater in your house to the electrical substation to the power plant.
Among the questions to be answered: How do the ants migrate across different computer platforms and systems operating at different speeds? How many ants should you have patrolling a system? How long do they live? How do the ants scale up to identify a threat and then ramp back down?
“In nature, we know that ants defend against threats very successfully,” Fulp said. “They can ramp up their defense rapidly, and then resume routine behavior quickly after an intruder has been stopped. We’re trying to achieve that same framework in a computer system.”
PNNL, a Department of Energy laboratory, conducts cutting-edge research in cyber security. Glenn Fink, a senior research scientist at PNNL, first came up with the idea of copying ant behavior for computer security. He was familiar with Fulp’s work developing faster computer scans using parallel processing — dividing computer data into batches like lines of shoppers going through grocery store checkouts, where each lane is focused on certain threats — and invited him to join the project several years ago.
Fulp and two of his students, Wes Featherstun and Brian Williams, then graduate students in computer science, worked at PNNL during the summer of 2009. Fulp and Crouse worked there again last summer.
