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DNA synthesis for true random number generation

Author

Listed:
  • Linda C. Meiser

    (ETH Zurich)

  • Julian Koch

    (ETH Zurich)

  • Philipp L. Antkowiak

    (ETH Zurich)

  • Wendelin J. Stark

    (ETH Zurich)

  • Reinhard Heckel

    (Technical University of Munich)

  • Robert N. Grass

    (ETH Zurich)

Abstract

The volume of securely encrypted data transmission required by today’s network complexity of people, transactions and interactions increases continuously. To guarantee security of encryption and decryption schemes for exchanging sensitive information, large volumes of true random numbers are required. Here we present a method to exploit the stochastic nature of chemistry by synthesizing DNA strands composed of random nucleotides. We compare three commercial random DNA syntheses giving a measure for robustness and synthesis distribution of nucleotides and show that using DNA for random number generation, we can obtain 7 million GB of randomness from one synthesis run, which can be read out using state-of-the-art sequencing technologies at rates of ca. 300 kB/s. Using the von Neumann algorithm for data compression, we remove bias introduced from human or technological sources and assess randomness using NIST’s statistical test suite.

Suggested Citation

  • Linda C. Meiser & Julian Koch & Philipp L. Antkowiak & Wendelin J. Stark & Reinhard Heckel & Robert N. Grass, 2020. "DNA synthesis for true random number generation," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-19757-y
    DOI: 10.1038/s41467-020-19757-y
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    Cited by:

    1. Tongtong Zhang & Lingzhi Wang & Jing Wang & Zhongqiang Wang & Madhav Gupta & Xuyun Guo & Ye Zhu & Yau Chuen Yiu & Tony K. C. Hui & Yan Zhou & Can Li & Dangyuan Lei & Kwai Hei Li & Xinqiang Wang & Qi W, 2023. "Multimodal dynamic and unclonable anti-counterfeiting using robust diamond microparticles on heterogeneous substrate," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Anne M. Luescher & Andreas L. Gimpel & Wendelin J. Stark & Reinhard Heckel & Robert N. Grass, 2024. "Chemical unclonable functions based on operable random DNA pools," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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