The Raspberry Pi can detect malware by scanning for EM waves

Raspberry Pi

Photo: Future Publishing / Getty (Getty Images)

The world’s largest companies are struggling with increasingly widespread and sophisticated malware attacks, but an interesting new malware detection technique can help companies counter these threats without having to use software.

A team of researchers at the French Research Institute of Computer Science and Random Systems created an anti-malware system centered around a Raspberry Pi that scans devices for electromagnetic waves. As reported by Toms hardware, the security device uses an oscilloscope (Picoscope 6407) and an H-Field probe connected to a Raspberry Pi 2B to detect abnormalities in specific electromagnetic waves emitted by computers under attack, a technique that researchers say is used for to “obtain accurate knowledge of malware type and identity.”

The detection system then relies on Convolution Neural Networks (CNN) to determine if the data collected indicates the presence of a threat. Using this technique, researchers claim that they could record 100,000 measurement traces from IoT devices infected with genuine malware samples and predicted three generic and one benign malware class with an accuracy as high as 99.82%.

Best of all, there is no need for software and the device you are scanning does not need to be tampered with in any way. As such, bad actors will not succeed in their attempts to hide malicious code from malware detection software using blurring techniques.

“Our method requires no modification of the target device. It can thus be implemented independently of the available resources without overhead. In addition, our approach has the advantage that it can hardly be detected and bypassed by malware authors,” researchers wrote in the newspaper.

Keep in mind that this system was created for research purposes, not to be released as a commercial product, though it may inspire security teams to explore new ways to use EM waves to detect malware. The research is currently in its early stages and the neural network needs to be further trained before it can have any practical application.

So far, the system is a unique approach to securing devices by making it difficult for malware writers to hide their code, but the technology is nowhere near being available to the public.

And while this may sound promising as a cheap way to detect malware given the use of a Raspberry Pi, the other EM wave scanning equipment costs several thousand dollars. Despite its limitations, it is encouraging to see that research is approaching such an important topic from a unique angle – who knows, this simple setup can one day help prevent the next big break.


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