41 research outputs found
Probabilistic Infinite Secret Sharing
The study of probabilistic secret sharing schemes using arbitrary probability
spaces and possibly infinite number of participants lets us investigate
abstract properties of such schemes. It highlights important properties,
explains why certain definitions work better than others, connects this topic
to other branches of mathematics, and might yield new design paradigms.
A probabilistic secret sharing scheme is a joint probability distribution of
the shares and the secret together with a collection of secret recovery
functions for qualified subsets. The scheme is measurable if the recovery
functions are measurable. Depending on how much information an unqualified
subset might have, we define four scheme types: perfect, almost perfect, ramp,
and almost ramp. Our main results characterize the access structures which can
be realized by schemes of these types.
We show that every access structure can be realized by a non-measurable
perfect probabilistic scheme. The construction is based on a paradoxical pair
of independent random variables which determine each other.
For measurable schemes we have the following complete characterization. An
access structure can be realized by a (measurable) perfect, or almost perfect
scheme if and only if the access structure, as a subset of the Sierpi\'nski
space , is open, if and only if it can be realized by a span
program. The access structure can be realized by a (measurable) ramp or almost
ramp scheme if and only if the access structure is a set
(intersection of countably many open sets) in the Sierpi\'nski topology, if and
only if it can be realized by a Hilbert-space program
Infinite Secret Sharing -- Examples
The motivation for extending secret sharing schemes to cases when either the
set of players is infinite or the domain from which the secret and/or the
shares are drawn is infinite or both, is similar to the case when switching to
abstract probability spaces from classical combinatorial probability. It might
shed new light on old problems, could connect seemingly unrelated problems, and
unify diverse phenomena.
Definitions equivalent in the finitary case could be very much different when
switching to infinity, signifying their difference. The standard requirement
that qualified subsets should be able to determine the secret has different
interpretations in spite of the fact that, by assumption, all participants have
infinite computing power. The requirement that unqualified subsets should have
no, or limited information on the secret suggests that we also need some
probability distribution. In the infinite case events with zero probability are
not necessarily impossible, and we should decide whether bad events with zero
probability are allowed or not.
In this paper, rather than giving precise definitions, we enlist an abundance
of hopefully interesting infinite secret sharing schemes. These schemes touch
quite diverse areas of mathematics such as projective geometry, stochastic
processes and Hilbert spaces. Nevertheless our main tools are from probability
theory. The examples discussed here serve as foundation and illustration to the
more theory oriented companion paper
Optimal Information Rate of Secret Sharing Schemes on Trees
The information rate for an access structure is the reciprocal of the load of the optimal secret sharing scheme for this structure. We determine this value for all trees: it is (2 - 1/c)(-1), where is the size of the largest core of the tree. A subset of the vertices of a tree is a core if it induces a connected subgraph and for each vertex in the subset one finds a neighbor outside the subset. Our result follows from a lower and an upper bound on the information rate that applies for any graph and happen to coincide for trees because of a correspondence between the size of the largest core and a quantity related to a fractional cover of the tree with stars
Entropy Region and Convolution
The entropy region is constructed from vectors of random variables by collecting Shannon entropies of all subvectors. Its shape is studied here by means of polymatroidal constructions, notably by convolution. The closure of the region is decomposed into the direct sum of tight and modular parts, reducing the study to the tight part. The relative interior of the reduction belongs to the entropy region. Behavior of the decomposition under self-adhesivity is clarified. Results are specialized and extended to the region constructed from four tuples of random variables. This and computer experiments help to visualize approximations of a symmetrized part of the entropy region. The four-atom conjecture on the minimal Ingleton score is refuted. © 2016 IEEE