CryptoDB
Accelerating TFHE with Sorted Bootstrapping Techniques
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| Conference: | ASIACRYPT 2025 |
| Abstract: | Fully Homomorphic Encryption (FHE) enables secure computation over encrypted data, offering a breakthrough in privacy-preserving computing. Despite its promise, the practical deployment of FHE has been hindered by the significant computational overhead, especially in general-purpose bootstrapping schemes. In this work, we build upon the recent advancements of~\cite{LY23} to introduce a variant of the functional/programmable bootstrapping. By carefully sorting the steps of the blind rotation, we reduce the overall number of external products without compromising correctness. To further enhance efficiency, we propose a novel modulus-switching technique that increases the likelihood of satisfying pruning conditions, reducing computational overhead. Extensive benchmarks demonstrate that our method achieves a speedup ranging from 1.75x to 8.28x compared to traditional bootstrapping and from 1.26x to 2.14x compared to~\cite{LY23} bootstrapping techniques. Moreover, we show that this technique is better adapted to the $\indcpad$ security model by reducing the performance downgrade it implies. |
BibTeX
@inproceedings{asiacrypt-2025-35962,
title={Accelerating TFHE with Sorted Bootstrapping Techniques},
publisher={Springer-Verlag},
author={Loris Bergerat and Jean-Baptiste Orfila and Samuel Tap and Adeline Roux-Langlois},
year=2025
}