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Faster Gaussian Lattice Sampling Using Lazy Floating-Point Arithmetic

  • Léo Ducas
  • Phong Q. Nguyen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7658)

Abstract

Many lattice cryptographic primitives require an efficient algorithm to sample lattice points according to some Gaussian distribution. All algorithms known for this task require long-integer arithmetic at some point, which may be problematic in practice. We study how much lattice sampling can be sped up using floating-point arithmetic. First, we show that a direct floating-point implementation of these algorithms does not give any asymptotic speedup: the floating-point precision needs to be greater than the security parameter, leading to an overall complexity Õ(n3) where n is the lattice dimension. However, we introduce a laziness technique that can significantly speed up these algorithms. Namely, in certain cases such as NTRUSign lattices, laziness can decrease the complexity to Õ(n2) or even Õ(n). Furthermore, our analysis is practical: for typical parameters, most of the floating-point operations only require the double-precision IEEE standard.

Keywords

Target Vector Security Parameter Online Phase Cryptology ePrint Archive Matrix Sign Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© International Association for Cryptologic Research 2012

Authors and Affiliations

  • Léo Ducas
    • 1
  • Phong Q. Nguyen
    • 2
    • 3
  1. 1.Dept. InformatiqueENSParisFrance
  2. 2.INRIAFrance
  3. 3.Institute for Advanced StudyTsinghua UniversityChina

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