Low cost microphones protect 3D printers from attack

August 16, 2017 //By Nick Flaherty
Low cost microphones protect 3D printers from attack
Researchers from the Georgia Institute of Technology and Rutgers University are using low cost microphones and digital signal processing to protect 3D printers from viruses and malware that can change what they print.

"These 3D printed components will be going into people, aircraft and critical infrastructure systems," said Raheem Beyah, the Motorola Foundation Professor and associate chair in Georgia Tech's School of Electrical and Computer Engineering (above). "Malicious software installed in the printer or control computer could compromise the production process. We need to make sure that these components are produced to specification and not affected by malicious actors or unscrupulous producers."

This becomes even more important with 3D printers producing entire circuit boards. 

The technique uses a low cost microphone and digital signal processing to compare the operation of the printer with a reference recording of a correct print. This can show up an incorrect or malicious print. The key is that the technique is independent of printer firmware and software in the controlling computer which may itself have been compromised.

The team tested the technique on three different types of 3D printer and a computer numerical control (CNC) machine using an artificial knee built from polyethylene.

One of the challenges is obtaining good acoustic data in the noisy environments where 3D printers typically operate. Operation of other 3D printers nearby cut the accuracy significantly, but Beyah believes that challenge can be addressed with additional signal processing. The technique will also be applied to additional types of printers, and to different materials.

The researchers also used other techniques to protect a printer. For a standard print, the extruder and other components should follow a consistent mechanical path that can be observed with low cost camera sensors. Variations from the expected path could indicate an attack.

A third element is to use the same gold nanorods that are used in medical scans. This uses Raman Spectroscopy and computed tomography (CT) to detect the location of the nanorods that had been mixed with the filament material. Variations from the expected location of those particles could indicate a quality problem with the component.

"The idea that additive manufacturing

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