TY - GEN
T1 - A BGV-Subroutined CKKS Bootstrapping Algorithm Without Sine Approximation
AU - Fan, Jingjing
AU - Zhang, Chi
AU - Tan, Zejiu
AU - Jiang, Zoe Lin
AU - Au, Man Ho
AU - Yiu, Siu Ming
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - Bootstrapping plays a critical role in fully homomorphic encryption (FHE) systems like BGV, BFV, and CKKS, enabling versatile leveled multiplication. While BGV and BFV utilize a digit extraction-based approach for bootstrapping, CKKS employs a scaled sine function to approximate the modular reduction operation, followed by homomorphic evaluation of sine functions using polynomials. This method introduces a fixed lower bound on approximation error. Rather than building on existing CKKS bootstrapping approaches, we propose an innovative alternative pathway that eliminates the need for sine function fitting in modular reduction approximation. Our method leverages BGV bootstrapping as a subroutine and introduces a ciphertext transformation technique to transform CKKS ciphertexts into BGV-compatible format, thereby enabling the integration of the BGV bootstrapping framework within the CKKS process. Such incorporation complements the existing result that BGV and BFV bootstrapping algorithms are equivalent and CKKS bootstrapping algorithm can serve as a subroutine in BFV bootstrapping algorithm. In addition, compared with the trivial way to construct a CKKS-subroutined BGV bootstrapping containing an intermediate transformation from BGV to BFV then to CKKS, we design a CKKS-subroutined BGV bootstrapping with a direct transformation. As a result, we point out the transformation among BGV, BFV and CKKS bootstrapping algorithms, enabling the optimization of each algorithm’s strengths and advantages.
AB - Bootstrapping plays a critical role in fully homomorphic encryption (FHE) systems like BGV, BFV, and CKKS, enabling versatile leveled multiplication. While BGV and BFV utilize a digit extraction-based approach for bootstrapping, CKKS employs a scaled sine function to approximate the modular reduction operation, followed by homomorphic evaluation of sine functions using polynomials. This method introduces a fixed lower bound on approximation error. Rather than building on existing CKKS bootstrapping approaches, we propose an innovative alternative pathway that eliminates the need for sine function fitting in modular reduction approximation. Our method leverages BGV bootstrapping as a subroutine and introduces a ciphertext transformation technique to transform CKKS ciphertexts into BGV-compatible format, thereby enabling the integration of the BGV bootstrapping framework within the CKKS process. Such incorporation complements the existing result that BGV and BFV bootstrapping algorithms are equivalent and CKKS bootstrapping algorithm can serve as a subroutine in BFV bootstrapping algorithm. In addition, compared with the trivial way to construct a CKKS-subroutined BGV bootstrapping containing an intermediate transformation from BGV to BFV then to CKKS, we design a CKKS-subroutined BGV bootstrapping with a direct transformation. As a result, we point out the transformation among BGV, BFV and CKKS bootstrapping algorithms, enabling the optimization of each algorithm’s strengths and advantages.
KW - BGV
KW - CKKS
KW - Fully Homomorphic Encryption
KW - bootstrapping
KW - bootstrapping approximation
UR - https://www.scopus.com/pages/publications/105021329659
U2 - 10.1007/978-981-95-3540-8_15
DO - 10.1007/978-981-95-3540-8_15
M3 - 会议稿件
AN - SCOPUS:105021329659
SN - 9789819535392
T3 - Lecture Notes in Computer Science
SP - 273
EP - 285
BT - Information and Communications Security - 27th International Conference, ICICS 2025, Proceedings
A2 - Han, Jinguang
A2 - Xiang, Yang
A2 - Cheng, Guang
A2 - Susilo, Willy
A2 - Chen, Liquan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 27th International Conference on Information and Communications Security, ICICS 2025
Y2 - 29 October 2025 through 31 October 2025
ER -