Please use this identifier to cite or link to this item: https://elib.vku.udn.vn/handle/123456789/4012
Title: Configurable Encryption and Decryption Architectures for CKKS-Based Homomorphic Encryption
Authors: Lee, Jaehyeok
Duong, Ngoc Phap
Lee, Hanho
Keywords: homomorphic encryption (HE)
Cheon-Kim-Kim-Song (CKKS)
ring learning with errors (RLWE)
number theoretic transform (NTT)
hardware architecture
Issue Date: Aug-2023
Publisher: MDPI
Abstract: With the increasing number of edge devices connecting to the cloud for storage and analysis, concerns about security and data privacy have become more prominent. Homomorphic encryption (HE) provides a promising solution by not only preserving data privacy but also enabling meaningful computations on encrypted data; while considerable efforts have been devoted to accelerating expensive homomorphic evaluation in the cloud, little attention has been paid to optimizing encryption and decryption (ENC-DEC) operations on the edge. In this paper, we propose efficient hardware architectures for CKKS-based ENC-DEC accelerators to facilitate computations on the client side. The proposed architectures are configurable to support a wide range of polynomial sizes with multiplicative depths (up to 30 levels) at a 128-bit security guarantee. We evaluate the hardware designs on the Xilinx XCU250 FPGA platform and achieve an average encryption time 23.7× faster than that of the well-known SEAL HE library. By reducing time complexity and improving the hardware utilization of cryptographic algorithms, our configurable CKKS-supported ENC-DEC hardware designs have the potential to greatly accelerate cryptographic processes on the client side in the post-quantum era.
Description: Sensors 2023, 23 (17), 7389
URI: https://doi.org/10.3390/s23177389
https://elib.vku.udn.vn/handle/123456789/4012
Appears in Collections:NĂM 2023

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