TY - JOUR
T1 - DNA synthesis for true random number generation
AU - Meiser, Linda C.
AU - Koch, Julian
AU - Antkowiak, Philipp L.
AU - Stark, Wendelin J.
AU - Heckel, Reinhard
AU - Grass, Robert N.
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12
Y1 - 2020/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85096174708&partnerID=8YFLogxK
U2 - 10.1038/s41467-020-19757-y
DO - 10.1038/s41467-020-19757-y
M3 - Article
C2 - 33208744
AN - SCOPUS:85096174708
SN - 2041-1723
VL - 11
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5869
ER -