• Media type: Text; E-Article; Electronic Conference Proceeding
  • Title: Improved Reduction from the Bounded Distance Decoding Problem to the Unique Shortest Vector Problem in Lattices
  • Contributor: Bai, Shi [Author]; Stehlé, Damien [Author]; Wen, Weiqiang [Author]
  • Published: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2016
  • Language: English
  • DOI: https://doi.org/10.4230/LIPIcs.ICALP.2016.76
  • Keywords: Lattices ; Sparsification ; Unique Shortest Vector Problem ; Bounded Distance Decoding Problem
  • Origination:
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  • Description: We present a probabilistic polynomial-time reduction from the lattice Bounded Distance Decoding (BDD) problem with parameter 1/( sqrt(2) * gamma) to the unique Shortest Vector Problem (uSVP) with parameter gamma for any gamma > 1 that is polynomial in the lattice dimension n. It improves the BDD to uSVP reductions of [Lyubashevsky and Micciancio, CRYPTO, 2009] and [Liu, Wang, Xu and Zheng, Inf. Process. Lett., 2014], which rely on Kannan's embedding technique. The main ingredient to the improvement is the use of Khot's lattice sparsification [Khot, FOCS, 2003] before resorting to Kannan's embedding, in order to boost the uSVP parameter.
  • Access State: Open Access