Protection against Counterfeiting Attacks in 3D Printing by Streaming Signature-embedded Manufacturing Process Instructions

12Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The emerging Manufacturing-as-a-Service (MaaS) paradigm democratizes manufacturing by connecting people and businesses with manufacturing requests to those with manufacturing resources, via a digital thread. However, the digital thread can be vulnerable to attacks such as counterfeiting, IP theft and sabotage. An approach based on embedding custom anti-counterfeiting signatures in the design files, on-the-fly, is presented to protect against counterfeiting attacks. An experimental study of the effect of geometric and dimensional variations of the signatures in printed components, as well as the effect of the variations on the read rates of the codes are reported. We conduct experiments using a polyjet printer with veroclear material to study the positional and dimensional variations introduced in the embedded signature and the resulting effect on the readability of the design. The results suggest that signatures with spherical units of size †0.25 mm embedded within 20 mm cubic components can be printed with location precision of ∼5% (about 0.1 mm), and dimensional deviation of the order of 0.01 mm. A statistical model is developed to show that these variations pose minimum interference on the readability of the signatures. Embedding of randomized signatures offers security by serving as anti-counterfeit marks in the final part, and makes it harder to reverse engineer and produce counterfeited parts.

Cite

CITATION STYLE

APA

Tiwari, A., Villasenor, E. J., Gupta, N., Reddy, N., Karri, R., & Bukkapatnam, S. T. S. (2021). Protection against Counterfeiting Attacks in 3D Printing by Streaming Signature-embedded Manufacturing Process Instructions. In AMSec 2021 - Proceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security, co-located with CCS 2021 (pp. 11–21). Association for Computing Machinery, Inc. https://doi.org/10.1145/3462223.3485620

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free