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International Conference on Cryptography, Network Security and Communication Technology (CNSCT)

A Secure Comparison Protocol Based on the SM2 Homomorphic Encryption Algorithm

Xiao Deng, Shutong Li, Yuxin Li, Baodong Qin

Published Jan 23, 2026• 0 citations
Publisher
DOI
10.1145/3802927.3802953

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Secure comparison is a fundamental problem in multiparty computation. There are two different parties, each holding an l-bit integer, denoted by a and b, respectively. The goal of secure comparison is to compute the order relationship between a and b, say (a>b)∈{0,1}, without revealing their inputs to any others. Since previous solutions based on homomorphic encryption need at least Ω(l) encryptions for each l-bit comparison, the total encryption time leads to a computational bottleneck for these protocols. This work presents a fast, semi-honest, secure comparison protocol based on the BFV encryption scheme. With its vector-like plaintext space, the number of required encryptions can be significantly reduced; actually, only six encryptions are needed for each comparison in our protocol. In other words, the proposed protocol can achieve the time complexity O˜(λ+l) for a given security parameter λ. As a result, 4096-bit integers can be securely compared within 12.08 ms, which is 280 times faster than the state-of-the-art homomorphic encryption-based secure comparison protocol. Furthermore, we can compare k pairs of l⋅k−1-bit integers with almost the same execution time as comparing l-bit integers and achieve higher throughput regardless of the compared integer size.
Abstract. We show how two existing paradigms for two-party secure function evaluation (SFE) in the semi-honest model can be combined securely and efficiently – those based on additively homomorphic encryption (HE) with those based on garbled circuits (GC) and vice versa. Additionally, we propose new GC constructions for addition, subtraction, multiplication, and comparison functions. Our circuits are approximately two times smaller (in terms of garbled tables) than previous constructions. This implies corresponding computation and communication improvements in SFE of functions using the above building blocks (including the protocols for combining HE and GC). Based on these results, we present efficient constant-round protocols for secure integer comparison, and the related problems of minimum selection and minimum distance, which are crucial building blocks of many cryptographic schemes such as privacy preserving biometric authentication (e.g., face recognition, fingerprint matching, etc).
A fully homomorphic encryption (FHE) scheme allows a client to encrypt and delegate its data to a server that performs computation on the encrypted data that the client can then decrypt. While FHE gives confidentiality to clients' data, it does not protect the server's input and computation. Nevertheless, FHE schemes are still helpful in building delegation protocols that reduce communication complexity, as the ciphertext's size is independent of the size of the computation performed on them. We can further extend FHE by a property called circuit privacy, which guarantees that the result of computing on ciphertexts reveals no information on the computed function and the inputs of the server. Thereby, circuit private FHE gives rise to round optimal and communication efficient secure two-party computation protocols. Unfortunately, despite significant efforts and much work put into the efficiency and practical implementations of FHE schemes, very little has been done to provide useful and practical FHE supporting circuit privacy. In this work, we address this gap and design the first randomized bootstrapping algorithm whose single invocation sanitizes a ciphertext and, consequently, serves as a tool to provide circuit privacy. We give an extensive analysis, propose parameters, and provide a C++ implementation of our scheme. Our bootstrapping can sanitize a ciphertext to achieve circuit privacy at an 80-bit statistical security level in between 1.3 and 0.9 seconds, depending which Gaussian sampling algorithm is used, and whether the parameter set targets a fast Fourier or a number theoretic transform-based implementation. In addition, we can perform non-sanitized bootstrapping in around 0.27 or 0.14 seconds. Crucially, we do not need to increase the parameters to perform computation before or after sanitization takes place. For comparison's sake, we revisit the Ducas-Stehlé washing machine method. In particular, we give a tight analysis, estimate efficiency, review old, and provide new parameters.