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Posted: Aug 01, 2016

Researchers offer solution to 3D-printing cybersecurity concerns

(Nanowerk News) In a news release and paper in late July, researchers at New York University raised multiple cybersecurity concerns related to 3D printing.
Specifically, they contended that the intentional incorporation of small defects or the alteration of the printing orientation of a part, among other things, could be performed to maliciously reduce the durability and suitability for use of 3D printed parts. Thus, under this scenario, a computer ‘hacker’ would be able to potentially cause injury, or at least loss of the value of the produced part in the real world.
Researchers at the University of North Dakota offer a solution to this problem. In a February, 2015 article in the journal Machines ("Initial Work on the Characterization of Additive Manufacturing (3D Printing) Using Software Image Analysis"), UND researcher Jeremy Straub demonstrates how model-based assessment can be used to detect issues with 3D printed parts. While this work was initially performed to detect defects due to material issues, equipment malfunction and happenstance, it is also applicable to preventing malicious attacks, as well.
“An independent detection system, using a model of the expected output as a baseline, would be able to identify defects created by maloperation as well as maliciously introduced ones,” commented Straub. “The level of separation that is practically required will depend on the severity of the impact of a defect, the likelihood of attack and what other countermeasures are in place to prevent or mitigate such an attack.”
The system proposed would still be reliant on the resolution of the sensors, a key concern raised by the NYU researchers. However, the technology can be used with any relevant and position-correlated pixel-based sensing technology, meaning that even microscope-detail-level imagery could be used to assess an object, if dictated for a given application. Object position issues and other larger changes to the expected printing results could also be easily detected. These would, of course, require a user to select the desired printing orientation and would not attempt to detect an orientation selection mistake made due to human error.
A UND-based team is working on commercializing this technology, at present, with support from a North Dakota Department of Commerce Venture Grant. This work is part of ongoing 3D printing research at the university.
Source: University of North Dakota
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