Access Structure Hiding Secret Sharing from Novel Set Systems and Vector Families
Vipin Singh Sehrawat, Yvo Desmedt

TL;DR
This paper introduces a novel secret sharing scheme that hides access structures using advanced set systems and vector families, enhancing privacy and security against adversaries.
Contribution
It constructs a new set-system and vector family to enable access structure hiding in secret sharing, a significant advancement over traditional models.
Findings
Supports exponentially many hidden access structures
Maximum share size is asymptotically optimal
Security relies on the Generalized Diffie-Hellman assumption
Abstract
Secret sharing provides a means to distribute shares of a secret such that any authorized subset of shares, specified by an access structure, can be pooled together to recompute the secret. The standard secret sharing model requires public access structures, which violates privacy and facilitates the adversary by revealing high-value targets. In this paper, we address this shortcoming by introducing \emph{hidden access structures}, which remain secret until some authorized subset of parties collaborate. The central piece of this work is the construction of a set-system with strictly greater than subsets of a set of elements. Our set-system is defined over , where is a non-prime-power, such that the size of each set in is divisible by but the sizes of their…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
