HERMES: Homomorphic Encryption over Residual Number System for Multi-level EvaluationS

Homomorphic encryption enables computations on the ciphertext to preserve data privacy. However, its practical deployment has been hindered by the significant computational overhead compared to the plaintext computations. In response to this challenge, we present HERMES, a novel hardware acceleration system designed to explore the computation flow of the CKKS homomorphic encryption bootstrapping process. Among the major contributions of our proposed architecture, we first analyze the properties of the CKKS computation data flow and propose a new scheduling strategy by partitioning the computation modules into general-purpose and special-purpose modular computation modules to allow smaller resource consumption and flexible scheduling. The computation modules are also reconfigurable to reduce the memory access overhead during the intermediate computation. We also optimize the CKKS computation dataflow to improve the regularity with reduced control overhead.

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Publication Details

Published
2024-10-27
DOI
https://doi.org/10.1145/3676536.3697124
Citations
1
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.35

Funders

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article

HERMES: Homomorphic Encryption over Residual Number System for Multi-level EvaluationS

Keshab K. Parhi, Antian Wang, Kaiyuan Zhang, Yingjie Lao
1 citations
Cryptography and Data Security
0.35
article

HERMES: Homomorphic Encryption over Residual Number System for Multi-level EvaluationS

Keshab K. Parhi, Antian Wang, Kaiyuan Zhang, Yingjie Lao
article en
1 citations

Abstract

Homomorphic encryption enables computations on the ciphertext to preserve data privacy. However, its practical deployment has been hindered by the significant computational overhead compared to the plaintext computations. In response to this challenge, we present HERMES, a novel hardware acceleration system designed to explore the computation flow of the CKKS homomorphic encryption bootstrapping process. Among the major contributions of our proposed architecture, we first analyze the properties of the CKKS computation data flow and propose a new scheduling strategy by partitioning the computation modules into general-purpose and special-purpose modular computation modules to allow smaller resource consumption and flexible scheduling. The computation modules are also reconfigurable to reduce the memory access overhead during the intermediate computation. We also optimize the CKKS computation dataflow to improve the regularity with reduced control overhead.

Tufts University (US), University of Minnesota (US), Purdue University Fort Wayne (US)
National Science Foundation
Openalex Percentile: Top 29%
Cryptography and Data Security
0.35
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HERMES: Homomorphic Encryption over Residual Number System for Multi-level EvaluationS — Keshab K. Parhi, Antian Wang, et al. · (2024) | TGRS Research Map | TGRS