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Abstract Imagine if it were possible to create 3D objects in the palm of your hand within seconds using only a single photonic chip. Although 3D printing has revolutionized the way we create in nearly every aspect of modern society, current 3D printers rely on large and complex mechanical systems to enable layer-by-layer addition of material. This limits print speed, resolution, portability, form factor, and material complexity. Although there have been recent efforts in developing novel photocuring-based 3D printers that utilize light to transform matter from liquid resins to solid objects using advanced methods, they remain reliant on bulky and complex mechanical systems. To address these limitations, we combine the fields of silicon photonics and photochemistry to propose the first chip-based 3D printer. The proposed system consists of only a single millimeter-scale photonic chip without any moving parts that emits reconfigurable visible-light holograms up into a simple stationary resin well to enable non-mechanical 3D printing. Furthermore, we experimentally demonstrate a stereolithography-inspired proof-of-concept version of the chip-based 3D printer using a visible-light beam-steering integrated optical phased array and visible-light-curable resin, showing 3D printing using a chip-based system for the first time. This work demonstrates the first steps towards a highly-compact, portable, and low-cost solution for the next generation of 3D printers.
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3D printer audio and vibration side channel dataset for vulnerability research in additive manufacturing security
This dataset provides a comprehensive set of side channels from fused deposition modeling 3D printers in order to enable the research in the security of additive manufacturing processes against side channel attacks. These attacks exploit indirect signal emanations from physical processes to extract information about a system. Our data was collected using two different methods (iPhone app and Teensy 4.0 sensor system) on two different 3D printers (Bambu Lab P1P and A1 mini), and consists of two types of data, audio data in the form of the recording of the 3D printer's sound while printing, and vibration data in the form of the linear acceleration in the cartesian coordinates. The dataset includes data from 12 different 3D objects that cover a wide variety of movements made while 3D printing. Along with the side channels this dataset includes the source computer-aided design files of the objects, as well as .gcode and .3mf files used by the printers.
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- PAR ID:
- 10579978
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Data in Brief
- Volume:
- 57
- Issue:
- C
- ISSN:
- 2352-3409
- Page Range / eLocation ID:
- 111002
- Subject(s) / Keyword(s):
- Side channels Side channel attacks Additive manufacturing 3D printing Cyber physical systems Cybersecurity
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.dib.2024.111002
