Raheem Beyah Christopher Moore, Georgia Tech
Raheem Beyah, the Motorola Foundation Professor and associate chair in Georgia Tech’s School of Electrical and Computer Engineering, is shown in a 3D printing lab at the Woodruff School of Mechanical Engineering.

Researchers Develop Methods to Detect Hacking in 3D Printers

As 3D printing continues to supplant traditional manufacturing processes, concern is growing over the software’s vulnerability to hackers.

Additive manufacturing (AM), also known as 3D printing, is replacing conventional fabrication processes in critical areas ranging from aerospace components to medical implants. But because AM relies on software to control the 3D printer, the technology could become a target for malicious attacks, as well as for unscrupulous operators who may cut corners.

To head off this problem, researchers from the Georgia Institute of Technology and Rutgers University recently developed a three-layer method of verifying that components created using AM have not been compromised. Their method uses acoustic and other physical techniques to confirm that the printer is operating as expected, and nondestructive inspection techniques to verify the correct location of gold nanorods buried in the parts. The validation technique is independent of printer firmware and software in the controlling computer. Beyond detecting malicious activity or quality problems, the technique could stop inadvertent production problems, thereby conserving materials and saving time.

“Many 3D printed components will go into people, aircraft, and critical infrastructure devices,” says Raheem Beyah, the Motorola Foundation 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 these components are made to specifications and not affected by malicious actors or unscrupulous producers.”

The three components of the new system include:

  • Acoustic measurements of the 3D printer in operation. When compared to a reference recording of a correct print, this acoustic monitoring, when used with an inexpensive microphone and filtering software, detects changes in the printer’s sound that may indicate installation of malicious software.
  • Physically tracking 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), researchers can detect the location of gold nanorods that had been mixed with the filament material used in the 3D printer. The researchers were inspired to use gold nanorods based on their use as a contrast agents for medical imaging techniques that detect tumors. Variations from the expected location of those particles in an AM part could indicate a quality problem with the component. The variations could result from malicious activity, or else from efforts to conserve printer materials. Plus, nanorods were tested to ensure they wouldn’t compromise the structural integrity of AM components. 

Researchers tested their technique on three different types of 3D printers and a computer numerical control (CNC) machine using a polyethylene knee prosthesis as a test case.

Now that they’ve demonstrated the feasibility of the techniques, the researchers plan to use the NSF funding to improve the validation methods and move them closer to application, with a focus on testing the resilience of the approach and its resistance to intrusion and malicious attack.

Among the challenges the researchers face ahead will be obtaining good acoustic data in the noisy environments where 3D printers typically operate. During the research, operation of other 3D printers near the one being observed significantly cut the accuracy of the test methods. But Beyah believes that can be overcome with additional signal processing. The technique will also be applied to additional types of printers, and to different materials.

“The idea that additive manufacturing processes could be compromised to intentionally hurt someone hasn’t really been considered with some of these applications,” Beyah says. “There is a good bit of room to improve the security of 3D printers, and we think that will start with applications that are closest to humans, such as implants and medical devices.”

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