**Lossy Chains and Fractional Secret Sharing**

*Yuval Ishai and Eyal Kushilevitz and Omer Strulovich*

**Abstract: **Motivated by the goal of controlling the amount of work required to
access a shared resource or to solve a cryptographic puzzle,
we introduce and study the related notions of {\em lossy chains} and {\em fractional secret sharing}.

Fractional secret sharing generalizes traditional secret sharing by allowing a fine-grained control over the amount of uncertainty about the secret. More concretely, a fractional secret sharing scheme realizes a fractional access structure $f:2^{[n]}\to [m]$ by guaranteeing that from the point of view of each set $T\subseteq [n]$ of parties, the secret is {\em uniformly} distributed over a set of $f(T)$ potential secrets. We show that every (monotone) fractional access structure can be realized. For {\em symmetric} structures, in which $f(T)$ depends only on the size of $T$, we give an efficient construction with share size $poly(n,\log m)$.

Our construction of fractional secret sharing schemes is based on the new notion of {\em lossy chains} which may be of independent interest. A lossy chain is a Markov chain $(X_0,\ldots,X_n)$ which starts with a random secret $X_0$ and gradually loses information about it at a rate which is specified by a {\em loss function} $g$. Concretely, in every step $t$, the distribution of $X_0$ conditioned on the value of $X_t$ should always be uniformly distributed over a set of size $g(t)$. We show how to construct such lossy chains efficiently for any possible loss function $g$, and prove that our construction achieves an optimal asymptotic information rate.

**Category / Keywords: **foundations / Secret sharing, Markov chains

**Publication Info: **The 30th Symposium on Theoretical Aspects of Computer Science (STACS 2013)

**Date: **received 24 Feb 2013

**Contact author: **yuvali at cs technion ac il

**Available format(s): **PDF | BibTeX Citation

**Version: **20130227:175347 (All versions of this report)

**Short URL: **ia.cr/2013/105

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