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Random fractal-enabled physical unclonable functions with dynamic AI authentication

Author

Listed:
  • Ningfei Sun

    (Beihang University
    National Center for Nanoscience and Technology & University of Chinese Academy of Sciences)

  • Ziyu Chen

    (Beihang University)

  • Yanke Wang

    (Karlsruhe Institute of Technology)

  • Shu Wang

    (National Center for Nanoscience and Technology & University of Chinese Academy of Sciences)

  • Yong Xie

    (Beihang University
    Beihang University)

  • Qian Liu

    (National Center for Nanoscience and Technology & University of Chinese Academy of Sciences)

Abstract

A physical unclonable function (PUF) is a foundation of anti-counterfeiting processes due to its inherent uniqueness. However, the self-limitation of conventional graphical/spectral PUFs in materials often makes it difficult to have both high code flexibility and high environmental stability in practice. In this study, we propose a universal, fractal-guided film annealing strategy to realize the random Au network-based PUFs that can be designed on demand in complexity, enabling the tags’ intrinsic uniqueness and stability. A dynamic deep learning-based authentication system with an expandable database is built to identify and trace the PUFs, achieving an efficient and reliable authentication with 0% “false positives”. Based on the roughening-enabled plasmonic network platform, Raman-based chemical encoding is conceptionally demonstrated, showing the potential for improvements in security. The configurable tags in mass production can serve as competitive PUF carriers for high-level anti-counterfeiting and data encryption.

Suggested Citation

  • Ningfei Sun & Ziyu Chen & Yanke Wang & Shu Wang & Yong Xie & Qian Liu, 2023. "Random fractal-enabled physical unclonable functions with dynamic AI authentication," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37588-5
    DOI: 10.1038/s41467-023-37588-5
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    References listed on IDEAS

    as
    1. Yuqing Gu & Chang He & Yuqing Zhang & Li Lin & Benjamin David Thackray & Jian Ye, 2020. "Gap-enhanced Raman tags for physically unclonable anticounterfeiting labels," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    2. Jung Woo Leem & Min Seok Kim & Seung Ho Choi & Seong-Ryul Kim & Seong-Wan Kim & Young Min Song & Robert J. Young & Young L. Kim, 2020. "Edible unclonable functions," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    3. Jie Yin & Mary C. Boyce, 2015. "Unique wrinkles as identity tags," Nature, Nature, vol. 520(7546), pages 164-165, April.
    4. Min Seok Kim & Gil Ju Lee & Jung Woo Leem & Seungho Choi & Young L. Kim & Young Min Song, 2022. "Revisiting silk: a lens-free optical physical unclonable function," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    5. Peter Aldhous, 2005. "Murder by medicine," Nature, Nature, vol. 434(7030), pages 132-134, March.
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    Cited by:

    1. Junfang Zhang & Rong Tan & Yuxin Liu & Matteo Albino & Weinan Zhang & Molly M. Stevens & Felix F. Loeffler, 2024. "Printed smart devices for anti-counterfeiting allowing precise identification with household equipment," Nature Communications, Nature, vol. 15(1), pages 1-9, December.

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