Paper 2024/1366

Adaptive Successive Over-Relaxation Method for a Faster Iterative Approximation of Homomorphic Operations

Abstract

Homomorphic encryption is a cryptographic technique that enables arithmetic operations to be performed on encrypted data. However, word-wise fully homomorphic encryption schemes, such as BGV, BFV, and CKKS schemes, only support addition and multiplication operations on ciphertexts. This limitation makes it challenging to perform non-linear operations directly on the encrypted data. To address this issue, prior research has proposed efficient approximation techniques that utilize iterative methods, such as functional composition, to identify optimal polynomials. These approximations are designed to have a low multiplicative depth and a reduced number of multiplications, as these criteria directly impact the performance of the approximated operations. In this paper, we propose a novel method, named as adaptive successive over-relaxation (aSOR), to further optimize the approximations used in homomorphic encryption schemes. Our experimental results show that the aSOR method can significantly reduce the computational effort required for these approximations, achieving a reduction of 2–9 times compared to state-of-the-art methodologies. We demonstrate the effectiveness of the aSOR method by applying it to a range of operations, including sign, comparison, ReLU, square root, reciprocal of m-th root, and division. Our findings suggest that the aSOR method can greatly improve the efficiency of homomorphic encryption for performing non-linear operations.