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arXiv · 2610.17711

Local Leakage Resilience of Shamir Secret Sharing: Below Half Threshold Rate

Abstract

We study the local leakage resilience of Shamir secret sharing, where an adversary leaks a bounded number of bits from every share. For $n$ parties and reconstruction threshold $k$ over a prime field $\mathbb{F}_p$ with $p>n$, we prove the following. (1) There is an absolute constant $c_{\mathrm{bh}}<1/2$ such that, for $k\ge c_{\mathrm{bh}}n$, Shamir sharing is resilient to arbitrary one-bit leakage from every share. The best previous threshold was $0.668n$. (2) For every fixed $0<δ<1/2$ and $k\ge(1/2+δ)n$, Shamir sharing is resilient to $\left\lfloor\fracδ{24}\log_2 n\right\rfloor$ bits of arbitrary local leakage per share. By a recent attack, this number of bits is optimal up to a constant factor depending on $δ$. (3) For every fixed threshold rate $c>0$ and $k\ge cn$, Shamir sharing is resilient to quadratic-residue leakage and to almost all local leakage functions of up to $η_c\log_2 p$ bits, for a constant $η_c>0$. All three results follow from one analytic framework, which we develop for generalized Reed--Solomon codes: local leakage from a uniform codeword is statistically close to the same leakage from independent uniform field elements. The framework expresses the leakage distance as the norm of a function on the leakage outputs. The Efron--Stein decomposition splits this function into orthogonal components indexed by supports of dual codewords. Two tools bound the components: list recovery of the dual code, which is ordinary list decoding for one-bit leakage, and a generalized von Neumann inequality for MDS systems of linear forms that retains linearly many Gowers norms. The first tool gives the result above half, the second gives the constant-rate result, and applying both to different ranges of supports in the same decomposition gives the result below half.

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BibTeXRIS

Hai H. Nguyen. 2026-10-13. Local Leakage Resilience of Shamir Secret Sharing: Below Half Threshold Rate. https://arxiv.org/abs/2610.17711

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