License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CCC.2020.36
URN: urn:nbn:de:0030-drops-125881
URL: https://drops.dagstuhl.de/opus/volltexte/2020/12588/
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Bennett, Huck ; Peikert, Chris

Hardness of Bounded Distance Decoding on Lattices in š“_p Norms

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LIPIcs-CCC-2020-36.pdf (0.6 MB)


Abstract

Bounded Distance Decoding BDD_{p,Ī±} is the problem of decoding a lattice when the target point is promised to be within an Ī± factor of the minimum distance of the lattice, in the š“_p norm. We prove that BDD_{p, Ī±} is NP-hard under randomized reductions where Ī± ā†’ 1/2 as p ā†’ āˆž (and for Ī± = 1/2 when p = āˆž), thereby showing the hardness of decoding for distances approaching the unique-decoding radius for large p. We also show fine-grained hardness for BDD_{p,Ī±}. For example, we prove that for all p āˆˆ [1,āˆž) ā§µ 2ā„¤ and constants C > 1, Īµ > 0, there is no 2^((1-Īµ)n/C)-time algorithm for BDD_{p,Ī±} for some constant Ī± (which approaches 1/2 as p ā†’ āˆž), assuming the randomized Strong Exponential Time Hypothesis (SETH). Moreover, essentially all of our results also hold (under analogous non-uniform assumptions) for BDD with preprocessing, in which unbounded precomputation can be applied to the lattice before the target is available. Compared to prior work on the hardness of BDD_{p,Ī±} by Liu, Lyubashevsky, and Micciancio (APPROX-RANDOM 2008), our results improve the values of Ī± for which the problem is known to be NP-hard for all p > pā‚ ā‰ˆ 4.2773, and give the very first fine-grained hardness for BDD (in any norm). Our reductions rely on a special family of "locally dense" lattices in š“_p norms, which we construct by modifying the integer-lattice sparsification technique of Aggarwal and Stephens-Davidowitz (STOC 2018).

BibTeX - Entry

@InProceedings{bennett_et_al:LIPIcs:2020:12588,
  author =	{Huck Bennett and Chris Peikert},
  title =	{{Hardness of Bounded Distance Decoding on Lattices in š“_p Norms}},
  booktitle =	{35th Computational Complexity Conference (CCC 2020)},
  pages =	{36:1--36:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-156-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{169},
  editor =	{Shubhangi Saraf},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12588},
  URN =		{urn:nbn:de:0030-drops-125881},
  doi =		{10.4230/LIPIcs.CCC.2020.36},
  annote =	{Keywords: Lattices, Bounded Distance Decoding, NP-hardness, Fine-Grained Complexity}
}

Keywords: Lattices, Bounded Distance Decoding, NP-hardness, Fine-Grained Complexity
Collection: 35th Computational Complexity Conference (CCC 2020)
Issue Date: 2020
Date of publication: 17.07.2020


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