SIMD-Aware Homomorphic Compression and Application to Private Database Query

TL;DR

This paper introduces a SIMD-optimized homomorphic compression scheme for private database queries, achieving superior compression rates and significantly faster performance compared to previous methods.

Contribution

The paper presents a novel homomorphic compression scheme that fully leverages SIMD techniques, offering optimal compression and efficient decompression for private database query applications.

Findings

Achieves 4.7x to 33.2x faster performance than previous methods.

Provides asymptotically optimal compression rates.

Ensures good decompression complexity.

Abstract

In a private database query scheme (PDQ), a server maintains a database, and users send queries to retrieve records of interest from the server while keeping their queries private. A crucial step in PDQ protocols based on homomorphic encryption is homomorphic compression, which compresses encrypted sparse vectors consisting of query results. In this work, we propose a new homomorphic compression scheme with PDQ as its main application. Unlike existing approaches, our scheme (i) can be efficiently implemented by fully exploiting homomorphic SIMD technique and (ii) enjoys both asymptotically optimal compression rate and asymptotically good decompression complexity. Experimental results show that our approach is 4.7x to 33.2x faster than the previous best results.