Abstract:
Additive manufacturing has opened the possibility of printing a 3D object by just having a blueprint and a 3D printer. This advent in technology has brought a cybersecuri...Show MoreMetadata
Abstract:
Additive manufacturing has opened the possibility of printing a 3D object by just having a blueprint and a 3D printer. This advent in technology has brought a cybersecurity challenge. This brings up a challenge to detect objects, henceforth called controlled objects (COs) that potentially infringe upon laws, authorship rights, and other legal constraints. It is desirable to detect the COs before starting the 3D printing process to prevent legal consequences. We propose a method for identification of COs in 3D print job based on application of 3D object descriptors/fingerprints. These descriptors reflect different properties of a 3D object design and identify whether the object is controlled or not. We consider only technical objects when the blueprint cannot change a lot. We propose a set of descriptors to efficiently store the information about the blueprint, and to make an effective search in the database of COs represented by their descriptors.
Published in: 2023 International Conference on Cyberworlds (CW)
Date of Conference: 03-05 October 2023
Date Added to IEEE Xplore: 06 December 2023
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