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FabAuth: Printed Objects Identification Using Resonant Properties of Their Inner Structures

Authors:

Takuya IndoAuthors Info & Claims

CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

Paper No.: LBW2215, Pages 1 - 6

https://doi.org/10.1145/3290607.3313005

Published: 02 May 2019 Publication History

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Abstract

We present a method we propose called FabAuth for identifying 3D-printed objects, which utilizes the differences in the resonant properties of such objects. We focus on changing the internal structures of each object made through a 3D printing process to assign a unique resonant property to it even if multiple objects have the same appearance. To identify the objects, the method identifies resonant property differences by using vibration that can pass through 3D-printed objects. The method can be applied even to low-filled 3D-printed objects as long as an acoustic wave can travel through the objects from one sensor to another. To validate the method's feasibility, we conducted a preliminary experiment to confirm whether it can be applied to low-filled 3D-printed objects and found that its average classification accuracy reached 92.2%.

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Cited By

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Yampolskiy MBates PSeifi MShamsaei N(2022)State of Security Awareness in the Additive Manufacturing Industry: 2020 SurveyProgress in Additive Manufacturing 202110.1520/STP164420210119(192-212)Online publication date: 1-Dec-2022
https://doi.org/10.1520/STP164420210119
ElSayed KDachowicz APanchal JYampolskiy MElovici YYung MYampolskiy M(2021)Information Embedding in Additive Manufacturing through Printing Speed ControlProceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security10.1145/3462223.3485623(31-37)Online publication date: 19-Nov-2021
https://dl.acm.org/doi/10.1145/3462223.3485623
Kubo YEguchi KAoki RBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)3D-Printed Object Identification Method using Inner Structure Patterns Configured by Slicer SoftwareExtended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3334480.3382847(1-7)Online publication date: 25-Apr-2020
https://dl.acm.org/doi/10.1145/3334480.3382847
Show More Cited By

Index Terms

FabAuth: Printed Objects Identification Using Resonant Properties of Their Inner Structures
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models

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Published In

CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

May 2019

3673 pages

ISBN:9781450359719

DOI:10.1145/3290607

General Chairs:
Stephen Brewster
University of Glasgow, Scotland, UK
,
Geraldine Fitzpatrick
TU Wien, Austria
,
Program Chairs:
Anna Cox
University College London, UK
,
Vassilis Kostakos
University of Melbourne, Australia

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 May 2019

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Abstract

Funding Sources

Japan Science and Technology Agency

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CHI '19

Sponsor:

SIGCHI

CHI '19: CHI Conference on Human Factors in Computing Systems

May 4 - 9, 2019

Glasgow, Scotland Uk

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Cited By

View all

Yampolskiy MBates PSeifi MShamsaei N(2022)State of Security Awareness in the Additive Manufacturing Industry: 2020 SurveyProgress in Additive Manufacturing 202110.1520/STP164420210119(192-212)Online publication date: 1-Dec-2022
https://doi.org/10.1520/STP164420210119
ElSayed KDachowicz APanchal JYampolskiy MElovici YYung MYampolskiy M(2021)Information Embedding in Additive Manufacturing through Printing Speed ControlProceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security10.1145/3462223.3485623(31-37)Online publication date: 19-Nov-2021
https://dl.acm.org/doi/10.1145/3462223.3485623
Kubo YEguchi KAoki RBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)3D-Printed Object Identification Method using Inner Structure Patterns Configured by Slicer SoftwareExtended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3334480.3382847(1-7)Online publication date: 25-Apr-2020
https://dl.acm.org/doi/10.1145/3334480.3382847
Dogan MFaruqi FChurchill AFriedman KCheng LSubramanian SMueller SBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)G-ID: Identifying 3D Prints Using Slicing ParametersProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376202(1-13)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376202
Le HNguyen M(2020)An Online Platform for Enhancing Learning Experiences with Web-Based Augmented Reality and Pictorial Bar CodeAugmented Reality in Education10.1007/978-3-030-42156-4_3(45-57)Online publication date: 27-May-2020
https://doi.org/10.1007/978-3-030-42156-4_3

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