numerical control machine using a polyethylene tibial knee prosthesis as a test case, they said. Beyond detecting malicious activity or quality problems, the technique also could stop inadvertent production problems, which has the potential to reduce materials waste, researchers said.
The team—which also includes Mehdi Javanmard, assistant professor in the Department of Electrical and Computer Engineering at Rutgers University— presented their research in mid-August at the USENIX Security Symposium in Vancouver.
Beyah said he believes the technique can be used to secure the additive manufacturing process across many industries, including for the production of aircraft parts, automobile parts, and artificial limbs. The team plans to continue their work to improve the system so it functions without limitations in various environments, he added.
“We’re now working to ensure that the technique is robust,” Beyah said. “For example, we did not consider the acoustic technique in a noisy environment. We’re looking at various signal-processing techniques to enable it to work in large print centers.”
Elizabeth Montalbano is a freelance writer who has written about technology and culture for more than 15 years. She currently resides in a village on the southwest coast of Portugal.