DNA synthesis for true random number generation.

Area of Science:

• Chemistry
• Computer Science
• Genomics

Background:

• Increasingly complex networks necessitate large volumes of securely encrypted data transmission.
• Ensuring the security of sensitive information exchange relies on robust encryption and decryption schemes.
• True random numbers are critical for guaranteeing the security of cryptographic processes.

Purpose of the Study:

• To present a novel method for generating large volumes of true random numbers using DNA synthesis.
• To evaluate the robustness and nucleotide distribution of commercial DNA synthesis methods for random number generation.
• To assess the quality and quantity of randomness obtainable from DNA-based random number generation.

Main Methods:

• Exploiting the stochastic nature of chemistry through the synthesis of DNA strands composed of random nucleotides.
• Comparing three commercial random DNA synthesis services to assess robustness and nucleotide distribution.
• Utilizing the von Neumann algorithm for data compression to mitigate bias.
• Employing NIST's statistical test suite to rigorously assess the randomness of the generated numbers.

Main Results:

• DNA synthesis can yield approximately 7 million gigabytes of randomness from a single synthesis run.
• Readout of DNA-based random numbers is achievable using current sequencing technologies at rates of approximately 300 kB/s.
• Commercial DNA synthesis methods show varying degrees of robustness and nucleotide distribution.

Conclusions:

• DNA synthesis presents a viable and scalable approach for generating the massive volumes of true random numbers required for modern cybersecurity.
• The von Neumann algorithm effectively removes bias, and NIST testing confirms the high quality of DNA-derived random numbers.
• This method offers a promising solution for enhancing the security of encrypted data transmission in complex networks.