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3D-printed object authentication using micro and macro surface textures and geometric features

Seal, Ankit

3D-printed object authentication using micro and macro surface textures and geometric features Thumbnail


Authors

Ankit Seal



Abstract

As the speed, quality, and affordability of additive manufacturing (AM) processes improve, more organisations and consumers are adopting the technology. Customising products, localising production, and lowering logistics are just a few of the primary advantages of AM. Because of these and other advantages, AM allows for a worldwide distributed manufacturing and supply chain involving several parties. This raises questions regarding the manufactured product's authenticity, and consequently its quality and reliability in use. In this research, we first explore the various hazards that exist in the additive manufacturing cyber-physical environment. The results highlight the security challenges for the AM supply chain. We then evaluate some of the currently implemented security measures to identify drawbacks and vulnerabilities in them. A core aspect of our investigation involves developing an algorithm that leverages extracted features to identify and characterize the unique signatures of glyphs and watermarks on the surface of 3D-printed objects. Based on the findings, the research then proposes three different levels of security that can be implemented and a novel authentication technique that utilises the intrinsic surface texture of the 3D-printed object. The experimental results and analysis demonstrate that the proposed method can successfully authenticate a 3-D printed object with high precision, as well as achieve a high level of security and
robustness.

Citation

Seal, A. 3D-printed object authentication using micro and macro surface textures and geometric features. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/10732100

Thesis Type Thesis
Deposit Date May 9, 2023
Publicly Available Date May 28, 2024
Public URL https://uwe-repository.worktribe.com/output/10732100
Award Date May 28, 2024

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