INCHE: High-Performance Encoding for Relational Databases through Incrementally Homomorphic Encryption

TL;DR

INCHE introduces an incrementally homomorphic encryption scheme that enhances performance by caching plaintext-ciphertext correlations, reducing computational overhead in relational database encryption while maintaining security.

Contribution

It proposes a novel incremental HE scheme that improves efficiency by reusing encrypted data, with proven security and practical implementation on standard benchmarks.

Findings

INCHE significantly reduces encryption time compared to traditional HE schemes.

The scheme maintains semantic security under CPA.

Experimental results show improved performance on TPC-H benchmark.

Abstract

Homomorphic encryption (HE) offers data confidentiality by executing queries directly on encrypted fields in the database-as-a-service (DaaS) paradigm. While fully HE exhibits great expressiveness but prohibitive performance overhead, a better balance between flexibility and efficiency can be achieved by partially HE schemes. Performance-wise, however, the encryption rate of state-of-the-art HE schemes is still orders of magnitude lower than the I/O throughput, rendering the HE scheme the performance bottleneck. This paper proposes INCHE, an incrementally homomorphic encryption scheme, which aims to boost the performance of HE schemes by incrementally encrypting fields in relational databases. The key idea of INCHE is to explore the intrinsic correlation between plaintexts and cache them for future reuse such that expensive HE primitives from plaintexts to ciphertexts are avoided. We prove the semantic security of INCHE under the chosen-plaintext attack (CPA) model and show that its time complexity is linear in the plaintext length. We implement an INCHE prototype by extending the Symmetria cryptosystem and verify its effectiveness on both randomly-generated data and the TPC-H benchmark.