2018
DOI: 10.1109/tc.2016.2642962
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On Practical Discrete Gaussian Samplers for Lattice-Based Cryptography

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Cited by 68 publications
(31 citation statements)
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“…There are several possible algorithms that utilise uniform numbers to return Gaussian distributed numbers and they differ from each other in terms of implementation speed, memory, and precision. Constant-time hardware architectures for a wide range of samplers have been proposed [15,21]. However, to date such proposals have been designed on a case-by-case basis and as yet there has been no proposal of a generic hardware design.…”
Section: Countermeasures Against Timing Attacksmentioning
confidence: 99%
“…There are several possible algorithms that utilise uniform numbers to return Gaussian distributed numbers and they differ from each other in terms of implementation speed, memory, and precision. Constant-time hardware architectures for a wide range of samplers have been proposed [15,21]. However, to date such proposals have been designed on a case-by-case basis and as yet there has been no proposal of a generic hardware design.…”
Section: Countermeasures Against Timing Attacksmentioning
confidence: 99%
“…• Knuth-Yao: The Knuth-Yao sampler is a tree-based algorithm for sampling from non-uniform distributions by using a minimal number of input uniform bits, close to the entropy of the probability distribution. The scheme has a very compact memory footprint, but needs additional data scrambling to make the generated Gaussian samples time-independent [7]- [10]. [11], [12].…”
Section: Error Samplers For Lattice-based Cryptographymentioning
confidence: 99%
“…As seen in Table I, at least 9 candidates employ DGS, using a variety of aforementioned methods, with sigmas ranging from 1.2 to 107. Hardware designs of samplers have explored constant-time implementations [8], [10], [16]. For signature schemes, usually requiring large sigmas, hierarchical CDT sampling has been proposed for compact, efficient sampling in hardware [17].…”
Section: Error Samplers For Lattice-based Cryptographymentioning
confidence: 99%
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“…Discrete Gaussian samplers are known to be susceptible to side-channel analysis [11], [12], hence avoiding this on-device is advantageous. Additionally, this also economises the overall hardware resources used, for example, the discrete Gaussian sampling module consumes ≈ 15% of the overall resources in for BLISS hardware design [5].…”
Section: Ideal Lattice-based Signaturesmentioning
confidence: 99%