Paper 2019/452

A Central Limit Framework for Ring-LWE Noise Analysis

Sean Murphy
Rachel Player
Abstract

This paper develops Central Limit arguments for analysing the noise in ciphertexts in two homomorphic encryption schemes that are based on Ring-LWE. The first main contribution of this paper is to present and evaluate an average-case noise analysis for the BGV scheme. Our approach relies on the recent work of Costache et al. (SAC 2023) that gives the approximation of a polynomial product as a multivariate Normal distribution. We show how this result can be applied in the BGV context and evaluate its efficacy. We find this average-case approach can much more closely model the noise growth in BGV implementations than prior approaches, but in some cases it can also underestimate the practical noise growth. Our second main contribution is to develop a Central Limit framework to analyse the noise growth in the homomorphic Ring-LWE cryptosystem of Lyubashevsky, Peikert and Regev (Eurocrypt 2013, full version). Our approach is very general: apart from finite variance, no assumption on the distribution of the noise is required (in particular, the noise need not be subgaussian). We show that our approach leads to tighter bounds for the probability of decryption failure than those of prior work.

Metadata
Available format(s)
PDF
Publication info
Published by the IACR in CIC 2024
Keywords
Ring-LWECentral Limit Theoremδ-subgaussiandecryption failure probabilityBGV cryptosystemhomomorphic encryption
Contact author(s)
s murphy @ rhul ac uk
History
2024-07-16: last of 11 revisions
2019-05-08: received
See all versions
Short URL
https://ia.cr/2019/452
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2019/452,
      author = {Sean Murphy and Rachel Player},
      title = {A Central Limit Framework for Ring-{LWE} Noise Analysis},
      howpublished = {Cryptology {ePrint} Archive, Paper 2019/452},
      year = {2019},
      url = {https://eprint.iacr.org/2019/452}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.