Scientists have developed a better way to recognize a common internet attack, improving detection by 90 percent compared to current methods.
RICHLAND, Washington —
“A threshold just doesn’t offer much insight or information about what it is really going on in your system,” said Subasi. “A simple threshold can easily miss actual attacks, with serious consequences, and the defender may not even be aware of what’s happening.” As principal investigator Kevin Barker said: “You don’t want to throttle the network yourself when there isn’t an attack underway.”To improve detection accuracy, the PNNL team sidestepped the concept of thresholds completely. Instead, the team focused on the evolution of entropy, a measure of disorder in a system.
The improvement isn’t due only to the avoidance of thresholds. To improve accuracy further, the PNNL team added a twist by not only looking at static entropy levels but also watching trends as they change over time.In addition, Subasi explored alternative options to calculate entropy. Many denial-of-service detectionrely on a formula known as Shannon entropy. Subasi instead settled on a formula known as Tsallis entropy for some of the underlying mathematics.
That’s because the Tsallis formula amplifies differences in entropy rates more than the Shannon formula. Think of how we measure temperature. If our thermometer had a resolution of 200 degrees, our outdoor temperature would always appear to be the same. But if the resolution were 2 degrees or less—like most thermometers—we’d detect dips and spikes many times each day. Subasi showed that it’s similar with subtle changes in entropy, detectable through one formula but not the other.
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