CryptoDB
Revisiting Key Decomposition Techniques for FHE: Simpler, Faster and More Generic
Authors: |
|
---|---|
Download: | |
Conference: | ASIACRYPT 2024 |
Abstract: | Ring-LWE based homomorphic encryption computations in large depth use a combination of two techniques: 1) decomposition of big numbers into small limbs/digits, and 2) efficient cyclotomic multiplications modulo $X^N+1$. It was long believed that the two mechanisms had to be strongly related, like in the full-RNS setting that uses a CRT decomposition of big numbers over an NTT-friendly family of prime numbers, and NTT over the same primes for multiplications. However, in this setting, NTT was the bottleneck of all large-depth FHE computations. A breakthrough result from Kim et al. (Crypto'2023) managed to overcome this limitation by introducing a second gadget decomposition and showing that it indeed shifts the bottleneck and renders the cost of NTT computations negligible compared to the rest of the computation. In this paper, we extend this result (far) beyond the Full-RNS settings and show that we can completely decouple the big number decomposition from the cyclotomic arithmetic aspects. As a result, we get modulus switching/rescaling for free. We verify both in theory and in practice that the performance of key-switching, external and internal products and automorphisms using our representation are faster than the one achieved by Kim et al., and we discuss the high impact of these results for low-level or hardware optimizations as well as the benefits of the new parametrizations for FHE compilers. We even manage to lower the running time of the gate bootstrapping of $\TFHE$ by eliminating one eighth of the FFTs and one sixth of the linear operations, which lowers the running time below 5.5ms on recent CPUs. |
BibTeX
@inproceedings{asiacrypt-2024-34657, title={Revisiting Key Decomposition Techniques for FHE: Simpler, Faster and More Generic}, publisher={Springer-Verlag}, author={Mariya Georgieva Belorgey and Sergiu Carpov and Nicolas Gama and Sandra Guasch and Dimitar Jetchev}, year=2024 }