Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-sparse Keys
Jean-Philippe Bossuat, Christian Mouchet, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux
摘要
We present a bootstrapping procedure for the full-RNS variant of the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17, SAC 18). Compared to the previously proposed procedures (Eurocrypt 18 & 19, CT-RSA 20), our bootstrapping procedure is more precise, more efficient (in terms of CPU cost and number of consumed levels), and is more reliable and 128-bit-secure. Unlike the previous approaches, it does not require the use of sparse secret-keys. Therefore, to the best of our knowledge, this is the first procedure that enables a highly efficient and precise bootstrapping with a low probability of failure for parameters that are 128-bit-secure under the most recent attacks on sparse R-LWE secrets.
We achieve this efficiency and precision by introducing three novel contributions: (i) We propose a generic algorithm for homomorphic polynomial-evaluation that takes into account the approximate rescaling and is optimal in level consumption. (ii) We optimize the key-switch procedure and propose a new technique for linear transformations (double hoisting). (iii) We propose a systematic approach to parameterize the bootstrapping, including a precise way to assess its failure probability.
We implemented our improvements and bootstrapping procedure in the open-source Lattigo library. For example, bootstrapping a plaintext in takes 18 seconds, has an output coefficient modulus of 505 bits, a mean precision of 19.1 bits, and a failure probability of . Hence, we achieve 14.1 improvement in bootstrapped throughput (plaintext-bit per second), with respect to the previous best results, and we have a failure probability 468 smaller and ensure 128-bit security.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper38
- CraterLake: a hardware accelerator for efficient unbounded computation on encrypted dataNikola Samardzic, Axel Feldmann, Aleksandar Krastev, Nathan Manohar 等ISCA 2022 · 被引用 205 次
- BTS: an accelerator for bootstrappable fully homomorphic encryptionSangpyo Kim, Jongmin Kim, Michael Jaemin Kim, Wonkyung Jung 等ISCA 2022 · 被引用 184 次
- Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel ConvolutionsEunsang Lee, Joon-Woo Lee, Junghyun Lee, Young-Sik Kim 等ICML 2022 · 被引用 171 次
- ARK: Fully Homomorphic Encryption Accelerator with Runtime Data Generation and Inter-Operation Key ReuseJongmin Kim, Gwangho Lee, Sangpyo Kim, Gina Sohn 等MICRO 2022 · 被引用 160 次
- BOLT: Privacy-Preserving, Accurate and Efficient Inference for TransformersQi Pang, Jinhao Zhu, Helen Möllering, Wenting Zheng 等S&P 2024 · 被引用 149 次
相关 Paper
- High-Precision Bootstrapping of RNS-CKKS Homomorphic Encryption Using Optimal Minimax Polynomial Approximation and Inverse Sine FunctionJoon-Woo Lee, Eunsang Lee, Yongwoo Lee, Young-Sik Kim 等EUROCRYPT 2021 · 被引用 110 次
- Efficient Bootstrapping in Fully Homomorphic Encryption for Matrix ArithmeticEric Crockett, Craig Gentry, Hyojun Kim, Yeongmin Lee 等CRYPTO 2026
- Leveraging Discrete CKKS to Bootstrap in High PrecisionHyeongmin Choe, Jaehyung Kim, Damien Stehlé, Elias SuvantoCCS 2025
- New Techniques for Fast and Shallow FHE Bootstrapping and BeyondAayush Jain, Huijia Lin, Zeyu Liu, Sagnik SahaCRYPTO 2026
- SHIP: A Shallow and Highly Parallelizable CKKS Bootstrapping AlgorithmJung Hee Cheon, Guillaume Hanrot, Jongmin Kim, Damien StehléEUROCRYPT 2025 · 被引用 8 次
