Three-layer technique for secure additive manufacturing

Because the additive manufacturing process relies on software to control the 3D printer, it could become a target for malicious attacks, as well as for unscrupulous operators who may cut corners.

Researchers from the Georgia Institute of Technology and Rutgers University have developed a three-layer system to verify that components produced using additive manufacturing have not been compromised. Their system uses acoustic and other physical techniques to confirm that the printer is operating as expected, and non-destructive inspection techniques to verify the correct location of tiny gold nanorods buried in the parts. The validation technique is independent of printer firmware and software in the controlling computer.

“These 3D printed components will be going into people, aircraft and critical infrastructure systems,” said Raheem Beyah, professor and associate chair in Georgia Tech's School of Electrical and Computer Engineering. “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.”

The three components of the new system include:

  • Acoustic measurement of the 3D printer in operation. When compared to a reference recording of a correct print, this acoustic monitoring can detect changes in the printer's sound that may indicate installation of malicious software.
  • Physical tracking of printer components. To create the desired object, the printer's extruder and other components should follow a consistent mechanical path that can be observed with inexpensive sensors. Variations from the expected path could indicate an attack.
  • Detection of nanorods in finished components. Using Raman Spectroscopy and computed tomography (CT), the researchers could detect the location of gold nanorods that had been mixed with the filament material used in the 3D printer. Variations from the expected location of those particles could indicate a quality problem with the component.

The researchers tested their technique on three different types of 3D printers and a CNC machine using a polyethylene tibial knee prosthesis as a test case. Beyond detecting malicious activity or quality problems, the technique could stop inadvertent production problems, reducing materials waste.

The gold contrast materials were tested to make sure they wouldn't compromise the structural integrity of the printed components.

The institutions now plan to use the funding recently awarded to them by the National Science Foundation to improve the validation methods and move them closer to application.

Among the challenges ahead will be obtaining good acoustic data in the noisy environments in which 3D printers typically operate. In their research the team reported that operation of other 3D printers near the one being observed cut the accuracy significantly, but Prof Beyah believes this can be addressed with additional signal processing. The technique will also be applied to additional types of printers, and to different materials.