Hermes: Efficient Global Homomorphic Aggregation over Mutable Packed Ciphertexts

Fuente: arXiv
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Main Author: Zhao, Dongfang
Format: Preprint
Published: 2025
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author Zhao, Dongfang
author_facet Zhao, Dongfang
contents Fully Homomorphic Encryption (FHE) promises the ability to compute over encrypted data without revealing sensitive contents. However, enabling high-frequency updates and statistical analysis in outsourced databases remains elusive due to the structural mismatch between mutable database records and the cryptographically expensive mutability of FHE ciphertexts. This paper presents Hermes, a prototype system tailored for efficient aggregation queries and dynamic tuple updates on homomorphically encrypted databases. The core design of Hermes is twofold. First, to amortize FHE costs and accelerate unconditional aggregations, Hermes introduces a SIMD-aware packed data model that embeds precomputed aggregate statistics directly into each ciphertext, enabling constant-time global aggregations without expensive Galois automorphisms. Second, to support true in-place mutability, we develop homomorphic algorithms based on polynomial slot masking and shifting, which are provably secure under the standard IND-CPA model. We scope Hermes to unconditional global aggregations to achieve both high performance and in-place updates simultaneously, two properties that prior FHE database systems have not delivered at scale. Hermes is implemented as a suite of C++ loadable functions in MySQL. Extensive evaluations on the TPC-H benchmark and three real-world datasets demonstrate significant performance improvements in query throughput, tuple insertions, and tuple deletions compared to conventional FHE implementations, validating its efficacy for highly dynamic and analytical workloads.
format Preprint
id arxiv_https___arxiv_org_abs_2506_03308
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hermes: Efficient Global Homomorphic Aggregation over Mutable Packed Ciphertexts
Zhao, Dongfang
Cryptography and Security
Databases
Fully Homomorphic Encryption (FHE) promises the ability to compute over encrypted data without revealing sensitive contents. However, enabling high-frequency updates and statistical analysis in outsourced databases remains elusive due to the structural mismatch between mutable database records and the cryptographically expensive mutability of FHE ciphertexts. This paper presents Hermes, a prototype system tailored for efficient aggregation queries and dynamic tuple updates on homomorphically encrypted databases. The core design of Hermes is twofold. First, to amortize FHE costs and accelerate unconditional aggregations, Hermes introduces a SIMD-aware packed data model that embeds precomputed aggregate statistics directly into each ciphertext, enabling constant-time global aggregations without expensive Galois automorphisms. Second, to support true in-place mutability, we develop homomorphic algorithms based on polynomial slot masking and shifting, which are provably secure under the standard IND-CPA model. We scope Hermes to unconditional global aggregations to achieve both high performance and in-place updates simultaneously, two properties that prior FHE database systems have not delivered at scale. Hermes is implemented as a suite of C++ loadable functions in MySQL. Extensive evaluations on the TPC-H benchmark and three real-world datasets demonstrate significant performance improvements in query throughput, tuple insertions, and tuple deletions compared to conventional FHE implementations, validating its efficacy for highly dynamic and analytical workloads.
title Hermes: Efficient Global Homomorphic Aggregation over Mutable Packed Ciphertexts
topic Cryptography and Security
Databases
url https://arxiv.org/abs/2506.03308