Paper 2024/1734 Original: eprint.iacr.org/2024/1734 ↗

Optimizing Message Range and Ciphertext Storage in GSW Encryption Using CRT and PVW-like Compression Scheme

Kung-Wei Hu
Huan-Chih Wang
Ja-Ling Wu
Abstract

This paper explores advancements in the Gentry-Sahai-Waters (GSW) fully homomorphic encryption scheme, addressing challenges related to message data range limitations and ciphertext size constraints. We introduce a novel approach utilizing the Chinese Remainder Theorem (CRT) for message decomposition, significantly expanding the allowable message range to the entire plaintext space. This method enables unrestricted message selection and supports parallel homomorphic operations without intermediate decryption. Additionally, we adapt existing ciphertext compression techniques, such as the PVW-like scheme, to reduce memory overhead associated with ciphertexts. Our experimental results demonstrate the effectiveness of the CRT-based decomposition in increasing the upper bound of message values and improving the scheme's capacity for consecutive homomorphic operations. However, compression introduces a trade-off, necessitating a reduced message range due to error accumulation. This research contributes to enhancing the practicality and efficiency of the GSW encryption scheme for complex computational scenarios while managing the balance between expanded message range, computational complexity, and storage requirements.

Metadata
Available format(s)
PDF
Category
Public-key cryptography
Publication info
Preprint.
History
2024-10-23: last updated
2024-10-23: published
Short URL
https://ia.cr/2024/1734
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2024/1734,
      author = {Kung-Wei Hu and Huan-Chih Wang and Ja-Ling Wu},
      title = {Optimizing Message Range and Ciphertext Storage in GSW Encryption Using CRT and PVW-like Compression Scheme},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/1734},
      year = {2024},
      url = {https://eprint.iacr.org/2024/1734}
}
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