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On the Lattice Smoothing Parameter Problem

Published 26 Dec 2014 in cs.CC | (1412.7979v1)

Abstract: The smoothing parameter ηϵ(L)\eta_{\epsilon}(\mathcal{L}) of a Euclidean lattice L\mathcal{L}, introduced by Micciancio and Regev (FOCS'04; SICOMP'07), is (informally) the smallest amount of Gaussian noise that "smooths out" the discrete structure of L\mathcal{L} (up to error ϵ\epsilon). It plays a central role in the best known worst-case/average-case reductions for lattice problems, a wealth of lattice-based cryptographic constructions, and (implicitly) the tightest known transference theorems for fundamental lattice quantities. In this work we initiate a study of the complexity of approximating the smoothing parameter to within a factor γ\gamma, denoted γ\gamma-GapSPP{\rm GapSPP}. We show that (for ϵ=1/poly(n)\epsilon = 1/{\rm poly}(n)): (2+o(1))(2+o(1))-GapSPP∈AM{\rm GapSPP} \in {\rm AM}, via a Gaussian analogue of the classic Goldreich-Goldwasser protocol (STOC'98); (1+o(1))(1+o(1))-GapSPP∈coAM{\rm GapSPP} \in {\rm coAM}, via a careful application of the Goldwasser-Sipser (STOC'86) set size lower bound protocol to thin spherical shells; (2+o(1))(2+o(1))-GapSPP∈SZK⊆AM∩coAM{\rm GapSPP} \in {\rm SZK} \subseteq {\rm AM} \cap {\rm coAM} (where SZK{\rm SZK} is the class of problems having statistical zero-knowledge proofs), by constructing a suitable instance-dependent commitment scheme (for a slightly worse o(1)o(1)-term); (1+o(1))(1+o(1))-GapSPP{\rm GapSPP} can be solved in deterministic 2<sup>O(n)</sup>polylog(1/ϵ)2<sup>{O(n)}</sup> {\rm polylog}(1/\epsilon) time and 2<sup>O(n)2<sup>{O(n)} space. As an application, we demonstrate a tighter worst-case to average-case reduction for basing cryptography on the worst-case hardness of the GapSPP{\rm GapSPP} problem, with O~(n)\tilde{O}(\sqrt{n}) smaller approximation factor than the GapSVP{\rm GapSVP} problem. Central to our results are two novel, and nearly tight, characterizations of the magnitude of discrete Gaussian sums.

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