Welcome to the resource topic for 2023/267
Title:
PROTEUS: A Tool to generate pipelined Number Theoretic Transform Architectures for FHE and ZKP applications
Authors: Florian Hirner, Ahmet Can Mert, Sujoy Sinha Roy
Abstract:Emerging cryptographic algorithms such as fully homomorphic encryption (FHE) and zero-knowledge proof (ZKP) perform arithmetic involving very large polynomials. One fundamental and time-consuming polynomial operation is the Number theoretic transform (NTT) which is a generalization of the fast Fourier transform. Hardware platforms such as FPGAs could be used to accelerate the NTTs in FHE and ZKP protocols. One major problem is that the FHE and ZKP protocols require different parameter sets, e.g., polynomial degree and coefficient size, depending on their applications. Therefore, a basic research question is: How to design scalable hardware architectures for accelerating NTTs in the FHE and ZKP protocols?
In this paper, we present ‘PROTEUS’, an open-source and parametric tool that generates synthesizable bandwidth-efficient NTT architectures for user-specified parameter sets. The architectures can be tuned to utilize different memory bandwidths and parameters which is a very important design requirement in both FHE and ZKP protocols. The generated NTT architectures show a significant performance speedup compared to similar NTT architectures on FPGA. Further comparisons with state-of-the-art show a reduction of up to 23% and 35% in terms of DSP and BRAM utilization.
ePrint: https://eprint.iacr.org/2023/267
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