A team of researchers from the Research Institute of Computer Science and Random Systems (IRISA) has developed a malware detection system using a Raspberry Pi that scans devices for specific electromagnetic (EM) waves. The group consists of Annelie Heuser, Matthieu Mastio, Duy-Phuc Pham, and Damien Marion .
Because the Pi focuses on the EM field, users don’t need to install anything on the target device. Instead, everything is handled via physical, external forces and is outside any software-level control potential malware has on a given machine.
The Raspberry Pi is trained with both safe and malicious data sets to help define the parameters of a potential threat. In addition, the Pi features an oscilloscope (Picoscope 6407) and an H-Field probe to detect EM field changes.
According to the research paper, the team used Convolution Neural Networks (CNN) to evaluate the data for threats. The model used to train the malware detection system provided accuracy as high as 99.82% during testing.
To get a closer look at this clever Raspberry Pi EM malware detection project, check out the official research paper created by the team.