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Medha: Microcoded Hardware Accelerator for computing on Encrypted Data. (arXiv:2210.05476v1 [cs.CR])
Oct. 12, 2022, 1:20 a.m. | Ahmet Can Mert, Aikata, Sunmin Kwon, Youngsam Shin, Donghoon Yoo, Yongwoo Lee, Sujoy Sinha Roy
cs.CR updates on arXiv.org arxiv.org
Homomorphic encryption (HE) enables computation on encrypted data, and hence
it has a great potential in privacy-preserving outsourcing of computations to
the cloud. Hardware acceleration of HE is crucial as software implementations
are very slow. In this paper, we present design methodologies for building a
programmable hardware accelerator for speeding up the cloud-side homomorphic
evaluations on encrypted data. First, we propose a divide-and-conquer technique
that enables homomorphic evaluations in a large polynomial ring $R_{Q,2N}$ to
use a hardware accelerator that …
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