Compile-Time Fully Homomorphic Encryption of Vectors: Eliminating Online Encryption via Algebraic Basis Synthesis

• URL: http://arxiv.org/abs/2505.12582v2
• Date: Thu, 22 May 2025 07:26:07 GMT
• Title: Compile-Time Fully Homomorphic Encryption of Vectors: Eliminating Online Encryption via Algebraic Basis Synthesis
• Authors: Dongfang Zhao,
• Abstract summary: ciphertexts are constructed from precomputed encrypted basis vectors combined with a runtime-scaled encryption of zero.<n>We formalize the method as a randomized $mathbbZ_t$- module morphism and prove that it satisfies IND-CPA security under standard assumptions.<n>Unlike prior designs that require a pool of random encryptions of zero, our construction achieves equivalent security using a single zero ciphertext multiplied by a fresh scalar at runtime.
• Score: 1.3824176915623292
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We propose a framework for compile-time ciphertext synthesis in fully homomorphic encryption (FHE) systems, where ciphertexts are constructed from precomputed encrypted basis vectors combined with a runtime-scaled encryption of zero. This design eliminates online encryption and instead relies solely on ciphertext-level additions and scalar multiplications, enabling efficient data ingestion and algebraic reuse. We formalize the method as a randomized $\mathbb{Z}_t$-module morphism and prove that it satisfies IND-CPA security under standard assumptions. The proof uses a hybrid game reduction, showing that adversarial advantage in distinguishing synthesized ciphertexts is negligible if the underlying FHE scheme is IND-CPA secure. Unlike prior designs that require a pool of random encryptions of zero, our construction achieves equivalent security using a single zero ciphertext multiplied by a fresh scalar at runtime, reducing memory overhead while preserving ciphertext randomness. The resulting primitive supports efficient integration with standard FHE APIs and maintains compatibility with batching, rotation, and aggregation, making it well-suited for encrypted databases, streaming pipelines, and secure compiler backends.

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