Please use this identifier to cite or link to this item: https://elib.vku.udn.vn/handle/123456789/4012
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dc.contributor.authorLee, Jaehyeok-
dc.contributor.authorDuong, Ngoc Phap-
dc.contributor.authorLee, Hanho-
dc.date.accessioned2024-07-30T08:44:23Z-
dc.date.available2024-07-30T08:44:23Z-
dc.date.issued2023-08-
dc.identifier.urihttps://doi.org/10.3390/s23177389-
dc.identifier.urihttps://elib.vku.udn.vn/handle/123456789/4012-
dc.descriptionSensors 2023, 23 (17), 7389vi_VN
dc.description.abstractWith 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.vi_VN
dc.language.isoenvi_VN
dc.publisherMDPIvi_VN
dc.subjecthomomorphic encryption (HE)vi_VN
dc.subjectCheon-Kim-Kim-Song (CKKS)vi_VN
dc.subjectring learning with errors (RLWE)vi_VN
dc.subjectnumber theoretic transform (NTT)vi_VN
dc.subjecthardware architecturevi_VN
dc.titleConfigurable Encryption and Decryption Architectures for CKKS-Based Homomorphic Encryptionvi_VN
dc.typeWorking Papervi_VN
Appears in Collections:NĂM 2023

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