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Research PaperResearchia:202610.09014

Improved Local Leakage Resilience of Shamir Secret Sharing and Worst-Case Optimal Polynomial Intersection

Yihang Sun

Abstract

We study two problems: Local Leakage Resilience (LLR) for Shamir secret sharing, and worst-case Optimal Polynomial Intersection (OPI). Both problems concern polynomials $Q(X)$ of degree less than $k$, over a prime-order finite field $\mathbb{F}_p$. In LLR for Shamir secret sharing, one asks how much one can learn about $Q(0)$ given a few bits leaked from each of $Q(α_1), \ldots, Q(α_n)$, for distinct non-zero evaluation points $α_i \in \mathbb{F}_p$. In OPI, one is given input list $S_1, \ldots,...

Submitted: October 9, 2026Subjects: Cybersecurity; Computer Science

Description / Details

We study two problems: Local Leakage Resilience (LLR) for Shamir secret sharing, and worst-case Optimal Polynomial Intersection (OPI). Both problems concern polynomials Q(X)Q(X) of degree less than kk, over a prime-order finite field Fp\mathbb{F}_p. In LLR for Shamir secret sharing, one asks how much one can learn about Q(0)Q(0) given a few bits leaked from each of Q(α1),…,Q(αn)Q(α_1), \ldots, Q(α_n), for distinct non-zero evaluation points αi∈Fpα_i \in \mathbb{F}_p. In OPI, one is given input list S1,…,Sn⊂FpS_1, \ldots, S_n \subset \mathbb{F}_p, and wants to find a polynomial Q(X)Q(X) of degree less than kk so that Q(αi)∈SiQ(α_i) \in S_i for as many ii as possible. Leveraging recent connection between these two problems due to (Sun, Wootters 2026), we improve the state-of-the-art for both problems. For LLR, we show that there is some constant δ>0δ> 0 so that, as long as R:=k/n≥1/2−δR := k/n \geq 1/2 - δ, Shamir secret-sharing is one-bit locally leakage resilient (meaning that one can learn only a negligible amount about Q(0)Q(0)). This is the first result to break the so-called "one-half barrier" for LLR, and improves over the previous best known result, requiring R≥0.668R \geq 0.668 (Kasser, 2025). For OPI, we give a quantum algorithm that finds a polynomial Q(X)Q(X) that agrees with at least a SCLρ(R)−ε\mathsf{SCL}_ρ(R)-\varepsilon fraction of the lists in expectation, for every fixed ε>0\varepsilon>0, where SCLρ\mathsf{SCL}_ρ is the \emph{semicircle law} of (Jordan et al., 2025). This improves previous algorithmic (and existential) results of (Jo, 2026) and (Horinaga, Yamakawa, 2026). We also give further improved existential results. We also adapt the hardness result of (Yamakawa, Zhandry, 2024) to apply to OPI (rather than a folded version); over large fields, this gives an unconditional separation between the quantum and classical hardness of OPI relative to a membership oracle.


Source: arXiv:2610.12357v1 - http://arxiv.org/abs/2610.12357v1 PDF: https://arxiv.org/pdf/2610.12357v1 Original Link: http://arxiv.org/abs/2610.12357v1

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Date:
Oct 9, 2026
Topic:
Computer Science
Area:
Cybersecurity
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