Paper 2026/418

A White-Box Bootstrapping Approach for High Precision Comparison Over Homomorphic Encryption

Abstract

We propose an efficient and numerically stable sign evaluation over the Cheon–Kim–Kim–Song (CKKS) homomorphic encryption (HE) scheme by introducing a new bootstrapping. Sign evaluation underpins applications such as comparison, sorting, and machine learning. Extensive studies exist, such as the polynomial-composition method by Lee et al. (IEEE TDSC'22). A critical oversight in the literature is that evaluating composite polynomials consumes substantial multiplicative depth, necessitating intermediate bootstrapping. Such bootstrapping introduces considerable noise, which harms convergence and degrades accuracy. Inspired by bootstrapping bits (Eurocrypt'24), we propose a new white-box bootstrapping for sign evaluation. We prove that our bootstrapping, unlike traditional bootstrapping, intrinsically reduces noise. Consequently, (i) it admits an interpretation as a polynomial composition, accelerating convergence “for free,” and (ii) it removes the bootstrapping-induced noise that disrupts convergence in prior art. Our implementation validates that the proposed method achieves approximately 40-bit precision—bounded only by the fundamental rescaling noise—doubling the $\approx$ 20 bits of prior work under identical parameters. Moreover, our approach requires less depth and is numerically more stable.