Scientists Develop Algorithm to Find Source of Malware, Spam and More
The algorithm helps determine the source using a relatively small number of sensors or observers.
Researcher Pedro Pinto and his colleagues at the Audiovisual Communications Laboratory of Switzerland's Ecole Polytechnique Fédérale de Lausanne (EPFL) recently developed an algorithm designed to determine the source of a threat.
"Until now, institutions such as the US National Security Agency (NSA) have used brute force methods to search for the sources of epidemic threats (malware, worms, trojans, internet rumours) in complex networks -- but scanning all potentially affected network nodes or address spaces requires a lot of time and resources," The H Security reports.
"If you would like to find the source of a virus, malware or spam-attack it is impossible to track the status of all nodes on the Internet, Pinto said in a telephone interview," writes Computerworld's Loek Essers. "'That would mean you would need about 1 billion sensors. And you don't want to monitor the entire Internet,' he added. Instead he and his colleagues devised an algorithm that shows that it is possible to estimate the location of the source from measurements collected by sparsely placed observers or sensors."
"Originally devised to pinpoint the source of real-world epidemics, the technique can easily be applied to computer networks -- no matter what their size is," Help Net Security's Zeljka Zorz writes. "And given that the Internet is a global system of interconnected computer networks, the application of this strategy seems only natural. The researchers tested the technique against for different types of network structures, and the results were satisfactory every time. Of course, the more connections the chosen nodes had, the smaller percentage of them had to be monitored and pumped for information."
"With so much research coming out to analyze data around crime, disease and other perils, it will be interesting to see the results when the work makes it way out of the lab and into the real world," writes GigaOM's Derrick Harris. "Death rumors on social media are often times just good fun, but using data science to stop the spread of an epidemic would really be something. Hopefully, public health, law enforcement and other officials are keeping up with the tools now at their disposal."