DNA synthesis for true random number generation

Linda C. Meiser, Julian Koch, Philipp L. Antkowiak, Wendelin J. Stark, Reinhard Heckel and Robert N. Grass ()
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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

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: 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.

Date: 2020
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DOI: 10.1038/s41467-020-19757-y

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