Raspberry Pi Can Detect Malware Using Electromagnetic Waves, Say Researchers

Raspberry Pi, a computer that is largely used for experimental pet projects by people can now be used to discover malware by employing the power of electromagnetic waves, researchers have found.

Using the single-board computer, the system can detect malware without requiring any software and with a whopping accuracy of nearly 100%.

Developed by a team from the Research Institute of Computer Science and Random Systems (IRISA) in France, the malware detection mechanism used Raspberry Pi to to scan devices for specific electromagnetic waves.

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How does Raspberry Pi's malware detection work?

Using an oscilloscope (Picoscope 6407) and H-Field probe with a Raspberry Pi 2B, researchers were able to use certain electromagnetic waves to find malware on any hardware. The team used Convolution Neural Networks (CNN) to assess malware threats.

The findings were revealed in a paper published last month. The authors claimed that their "method does not require any modification on the target device" and that it can be "deployed independently from the resources available without any overhead."

Also read:?Beware! Fake Telegram Messenger Apps Attacking PCs With Dangerous Malware

In addition, their method cannot be detected by hackers and those who may have deployed malware.

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The researchers claimed to have recorded ?100,000 traces of an Internet of Things (IoT) device that was infected with multiple malware samples. Their mechanism worked - for the team was able to predict three common types of malware with an accuracy of 99.82%.

Unfortunately, the system is designed for research purposes and may never be commercialised. If used in large-scale settings, it may help big companies avoid attacks and find ways to avoid being infected with malware.

Also read:?'Diavol' Ransomware Virus Hacks PC Via Email, And Blackmails You To Pay Money

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What do you think about this ingenious way to find malware? Let us know in the comments below.?For more in the world of?technology?and?science, keep reading?Indiatimes.com.

References

Pham, D. P., Marion, D., Mastio, M., & Heuser, A. (2021). Obfuscation Revealed: Leveraging Electromagnetic Signals for Obfuscated Malware Classification. Annual Computer Security Applications Conference.?