DNA synthesis for true random number generation.
- Meiser LC Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, CH-8093, Zurich, Switzerland.
- Koch J Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, CH-8093, Zurich, Switzerland.
- Antkowiak PL Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, CH-8093, Zurich, Switzerland.
- Stark WJ Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, CH-8093, Zurich, Switzerland.
- Heckel R Department of Electrical and Computer Engineering, Technical University of Munich, Arcistrasse 21, 80333, Munich, Germany.
- Grass RN Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, CH-8093, Zurich, Switzerland. rograss@ethz.ch.
- 2020-11-19
Published in:
- Nature communications. - 2020
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy
General Chemistry
English
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.
- Language
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- English
- Open access status
- gold
- Identifiers
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- DOI 10.1038/s41467-020-19757-y
- PMID 33208744
- Persistent URL
- https://folia.unifr.ch/global/documents/158669
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