Paper 2025/809
Don’t be mean: Reducing Approximation Noise in TFHE through Mean Compensation
, KU Leuven, KU Leuven, KU LeuvenAbstract
Fully Homomorphic Encryption (FHE) allows computations on encrypted data without revealing any information about the data itself. However, FHE ciphertexts include noise for security reasons, which increases during operations and can lead to decryption errors. This paper addresses the noise introduced during bootstrapping in Torus Fully Homomorphic Encryption (TFHE), particularly focusing on approximation errors during modulus switching and gadget decomposition. We propose a mean compensation technique that removes the mean term from the noise equations, achieving up to a twofold reduction in noise variance. This method can be combined with bootstrap key unrolling for further noise reduction. Mean compensation can reduce the error probability of a standard parameter set from
Metadata
- Available format(s)
-
PDF
- Category
- Implementation
- Publication info
- Preprint.
- Keywords
- Fully homomorphic encryptionNoise analysisModulus switchingGadget decompositionBootstrap key unrolling
- Contact author(s)
-
thomas deruijter @ esat kuleuven be
janpieter danvers @ esat kuleuven be
ingrid verbauwhede @ esat kuleuven be - History
- 2025-05-09: approved
- 2025-05-06: received
- See all versions
- Short URL
- https://ia.cr/2025/809
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2025/809,
author = {Thomas de Ruijter and Jan-Pieter D'Anvers and Ingrid Verbauwhede},
title = {Don’t be mean: Reducing Approximation Noise in {TFHE} through Mean Compensation},
howpublished = {Cryptology {ePrint} Archive, Paper 2025/809},
year = {2025},
url = {https://eprint.iacr.org/2025/809}
}
