[Resource Topic] 2017/298: An Investigation of Sources of Randomness Within Discrete Gaussian Sampling

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Title:
An Investigation of Sources of Randomness Within Discrete Gaussian Sampling

Authors: Séamus Brannigan, Neil Smyth, Tobias Oder, Felipe Valencia, Elizabeth O’Sullivan, Tim Güneysu, Francesco Regazzoni

Abstract:

This paper presents a performance and statistical analysis of random number generators and discrete Gaussian samplers implemented in software. Most Lattice-based cryptographic schemes utilise discrete Gaussian sampling and will require a quality random source. We examine a range of candidates for this purpose, including NIST DRBGs, stream ciphers and well-known PRNGs. The performance of these random sources is analysed within 64-bit implementations of Bernoulli, CDT and Ziggurat sampling. In addition we perform initial statistical testing of these samplers and include an investigation into improper seeding issues and their effect on the Gaussian samplers. Of the NIST approved Deterministic Random Bit Generators (DRBG), the AES based CTR-DRBG produced the best balanced performance in our tests.

ePrint: https://eprint.iacr.org/2017/298

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