Security of additive manufacturing: Attack taxonomy and survey

Yampolskiy, Mark; King, Wayne E.; Gatlin, Jacob; Belikovetsky, Sofia; Brown, Adam; Skjellum, Anthony; Elovici, Yuval

doi:10.1016/j.addma.2018.03.015

Cited by 93 publications

(59 citation statements)

References 43 publications

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“…This form of protection is commonly cited as an advantage of modularization (Sanchez and Mahoney, 1996;Baldwin and Henkel, 2015). Going forward, this concern may necessitate suitable technological solutions offering encryption and verification functionalities (Engelmann et al, 2018;Yampolskiy et al, 2018).…”

Section: Limitations and Future Researchmentioning

confidence: 99%

Creativity and productivity in product design for additive manufacturing: Mechanisms and platform outcomes of remixing

Friesike

Flath

Wirth

et al. 2019

J of Ops Management

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The present study explores the phenomenon of remixing in product design for additive manufacturing (AM). In contrast to other manufacturing techniques, AM offers unprecedented flexibility in adapting existing product designs to changing requirements. However, in order to benefit from this potential, structured design procedures and tools are indispensable. As a possible solution, online platforms for collaborative 3D model creation are increasingly implementing features for remixing, a concept describing the creation of new models on the foundation of existing design elements. Against this backdrop, the objective of this research is to provide evidence for the value of remixing as an organizational intervention for improving product design processes. To this end, we present a mixed methods approach using data from Thingiverse, the world's largest AM‐related online community. In a first step, we investigate qualitative data from 81 individual remix‐based designs to identify the underlying mechanisms of remixing. We identify six such mechanisms that can further be grouped by the intended outcome of the respective process (creativity‐oriented: inspiration, play, learning; productivity‐oriented: speed, improvement, empowerment). In a second step, we turn to a quantitative analysis of platform data, which indicates that remixing may lead to better design process outcomes in terms of quantity and diversity of designs. Furthermore, we find that designs created by remixing designers are significantly more often printed by community members suggesting that remixing helps ensure manufacturing compatibility akin to continuous process improvement. Our research has several implications for individual designers and organizations engaging with product design for AM.

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Section: Limitations and Future Researchmentioning

confidence: 99%

Creativity and productivity in product design for additive manufacturing: Mechanisms and platform outcomes of remixing

Friesike

Flath

Wirth

et al. 2019

J of Ops Management

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show abstract

“…For this paper, only sabotage attacks and related literature are of relevance. It should be noted that, by the end of 2017, no publications have addressed security of composite materials [34].…”

Section: Related Workmentioning

confidence: 99%

Optimal sabotage attack on composite material parts

Ranabhat

Clements

Gatlin

et al. 2019

International Journal of Critical Infrastructure Protection

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“…In contrast, the digital files are inserted in a 3D printer and the outcome is not dependent on the skill of a person, which is a major advantage for AM methods. However, such simplicity of the manufacturing step presents many security concerns in the AM process chain . It is a possibility that stolen CAD files can be used to print a component of exactly the same quality and functionality as the original component .…”

Section: Introductionmentioning

confidence: 99%

Embedding Tracking Codes in Additive Manufactured Parts for Product Authentication

et al. 2018

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Additive manufacturing (AM) process chain relies heavily on cloud resources and software programs. Cybersecurity has become a major concern for such resources. AM produces physical components, which can be compromised for quality by many other means and can be reverse engineered for unauthorized reproduction. This work is focused on taking advantage of layer-by-layer manufacturing process of AM to embed codes inside the components and reading them using image acquisition methods. The example of a widely used QR code format is used, but the same scheme can be used for other formats or alphanumeric strings. The code is segmented in a large number of parts for obfuscation. The results show that segmentation and embedding the code in numerous layers help in eliminating the effect of embedded features on the mechanical properties of the part. Such embedded codes can be used for parts produced by fused filament fabrication, inkjet printing, and selective laser sintering technologies for product authentication and identification of counterfeits. Post processing methods such as heat treatments and hot isostatic pressing may remove or distort these codes; therefore, analysis of AM method and threat level is required to determine if the proposed strategy can be useful for a particular product.

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Security of additive manufacturing: Attack taxonomy and survey

Cited by 93 publications

References 43 publications

Creativity and productivity in product design for additive manufacturing: Mechanisms and platform outcomes of remixing

Creativity and productivity in product design for additive manufacturing: Mechanisms and platform outcomes of remixing

Optimal sabotage attack on composite material parts

Embedding Tracking Codes in Additive Manufactured Parts for Product Authentication

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