The spread of Internet worms could be stopped early on by using a new method to watch computers for the behavior exhibited by infected hosts, according to research recently published in IEEE Transactions on Dependable and Secure Computing. Although other methods exist to protect against worms, the new strategy is designed to minimize interference with users’ normal work patterns, says Ness Shroff, a professor in the electrical-engineering department at Ohio State University, who was involved in the research. The researchers envision the technique being used in corporate networks, where it could identify computers that need to be quarantined and checked for infection.
Internet worms can be enlisted to launch denial-of-service attacks, which flood a website so that legitimate users can’t access it, or install back doors that can be used to create botnets. Large numbers of infected computers could significantly slow Internet traffic, even if the worms do nothing more than spread.
The Purdue University and Ohio State method of preventing worms from spreading works primarily for a class of worms that scans the Internet randomly in search of vulnerable host machines to infect. One such worm was Code Red, which infected more than 359,000 computers in less than 14 hours in 2001, and ultimately caused an estimated $2.6 billion in damages. Although this type of worm has been around for some time, Kurt Rohloff, a scientist in the distributed systems technology group at BBN Technologies, says that it is still dangerous. These “are a very simple class of worms that’s very easy to develop and program, but at the same time, they’re not as easy to contain,” he says. “If we could understand these fairly simple but still problematic worms, we could hopefully address the more so-called devious worms.”
The researchers base their strategy on a new model that they designed for how worms spread. Many existing models are based on an analogy to the spread of epidemics, Shroff says, but they are more accurate at later stages of an infection. The researchers’ model was particularly designed for accuracy in the early stages of infection, and it revealed that the key to whether or not a worm can spread successfully is the total number of times that an infected host scans the Internet in attempts to find new hosts to infect.
While other methods of containing worms have focused on monitoring computers for changes in the rate at which they scan the Internet from moment to moment, Shroff says that this can interfere with users’ daily activities. “Scan rates fluctuate a lot, so if you go online, you may scan a lot of times during a very short period of time, and then not scan at all,” he says. “We felt that the scan rate was too restrictive and could interfere with the normal operation of the network.” By monitoring the volume of scans over a longer period of time, he says, it’s possible to contain worms while keeping the threshold too high for ordinary users to raise alarms. Software could monitor the number of scans each computer on a network sends and quarantine any computers that exceed that number. Shroff hopes that changing the criteria for suspecting infection in this way will reduce the likelihood that legitimate scans of the Internet would be flagged as worm activity.