Paper 2026/2146

Succinct Shortness Check Under a Few Kilobytes via Tensor Train Random Projections

Abstract

Range proofs are a fundamental building block of lattice-based proof systems. Existing approaches relying on standard Johnson-Lindenstrauss (JL) struggle to provide succinctness: unstructured JL incurs linear verifier complexity, while structured JL introduced in RoK and Roll [ASIACRYPT'25] produce large projection vectors that need to be sent in costly committed form. For a witness of dimension $m$ and a security parameter $\lambda$, the JL projection vector is $O(\lambda),$ but the projection matrix is $O(\lambda m)$. Structured JL can be represented in $\widetilde O(\rho \lambda^2)$, but the resulting projection length grows to $\widetilde O(m / \rho)$ for any trade-off parameter $\rho > 1$. \hspace{5mm} In this paper, we introduce Tensor Train Random Projection (TTRP) to lattice-based cryptography, offering a ``best of both world" structured JL variant. The Tensor Train (TT) matrix representation drops to $\widetilde O(\lambda)$, while maintaining the projection vector at $O(\lambda)$. \hspace{5mm} We show that TTRP can be seamlessly integrated into proof systems by linearizing the well-formedness of the projection with the sum-check protocol. Concretely, using TTRP + sum-check as a drop-in replacement for existing range proof techniques yields an approximate shortness check with $O(\lambda \log m (\log\log m)^2)$ verifier complexity and proof size around $4$ KB for relevant parameter settings.