Lossiness and entropic hardness for ring-LWE

Zvika Brakerski, Nico Döttling

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The hardness of the Ring Learning with Errors problem (RLWE) is a central building block for efficiency-oriented lattice-based cryptography. Many applications use an “entropic” variant of the problem where the so-called “secret” is not distributed uniformly as prescribed but instead comes from some distribution with sufficient min-entropy. However, the hardness of the entropic variant has not been substantiated thus far. For standard LWE (not over rings) entropic results are known, using a “lossiness approach” but it was not known how to adapt this approach to the ring setting. In this work we present the first such results, where entropic security is established either under RLWE or under the Decisional Small Polynomial Ratio (DSPR) assumption which is a mild variant of the NTRU assumption. In the context of general entropic distributions, our results in the ring setting essentially match the known lower bounds (Bolboceanu et al., Asiacrypt 2019; Brakerski and Döttling, Eurocrypt 2020).

Original languageEnglish
Title of host publicationTheory of Cryptography - 18th International Conference, TCC 2020, Proceedings
EditorsRafael Pass, Krzysztof Pietrzak
PublisherSpringer Science and Business Media B.V.
Pages1-27
Number of pages27
ISBN (Electronic)978-3-030-64375-1
ISBN (Print)9783030643744
DOIs
StatePublished - 2020
Event18th International Conference on Theory of Cryptography, TCCC 2020 - Durham, United States
Duration: 16 Nov 202019 Nov 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12550 LNCS

Conference

Conference18th International Conference on Theory of Cryptography, TCCC 2020
Country/TerritoryUnited States
CityDurham
Period16/11/2019/11/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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