28 research outputs found
An Epitome of Multi Secret Sharing Schemes for General Access Structure
Secret sharing schemes are widely used now a days in various applications,
which need more security, trust and reliability. In secret sharing scheme, the
secret is divided among the participants and only authorized set of
participants can recover the secret by combining their shares. The authorized
set of participants are called access structure of the scheme. In Multi-Secret
Sharing Scheme (MSSS), k different secrets are distributed among the
participants, each one according to an access structure. Multi-secret sharing
schemes have been studied extensively by the cryptographic community. Number of
schemes are proposed for the threshold multi-secret sharing and multi-secret
sharing according to generalized access structure with various features. In
this survey we explore the important constructions of multi-secret sharing for
the generalized access structure with their merits and demerits. The features
like whether shares can be reused, participants can be enrolled or dis-enrolled
efficiently, whether shares have to modified in the renewal phase etc., are
considered for the evaluation
Secret Sharing Based on a Hard-on-Average Problem
The main goal of this work is to propose the design of secret sharing schemes
based on hard-on-average problems. It includes the description of a new
multiparty protocol whose main application is key management in networks. Its
unconditionally perfect security relies on a discrete mathematics problem
classiffied as DistNP-Complete under the average-case analysis, the so-called
Distributional Matrix Representability Problem. Thanks to the use of the search
version of the mentioned decision problem, the security of the proposed scheme
is guaranteed. Although several secret sharing schemes connected with
combinatorial structures may be found in the bibliography, the main
contribution of this work is the proposal of a new secret sharing scheme based
on a hard-on-average problem, which allows to enlarge the set of tools for
designing more secure cryptographic applications
Fourier-based Function Secret Sharing with General Access Structure
Function secret sharing (FSS) scheme is a mechanism that calculates a
function f(x) for x in {0,1}^n which is shared among p parties, by using
distributed functions f_i:{0,1}^n -> G, where G is an Abelian group, while the
function f:{0,1}^n -> G is kept secret to the parties. Ohsawa et al. in 2017
observed that any function f can be described as a linear combination of the
basis functions by regarding the function space as a vector space of dimension
2^n and gave new FSS schemes based on the Fourier basis. All existing FSS
schemes are of (p,p)-threshold type. That is, to compute f(x), we have to
collect f_i(x) for all the distributed functions. In this paper, as in the
secret sharing schemes, we consider FSS schemes with any general access
structure. To do this, we observe that Fourier-based FSS schemes by Ohsawa et
al. are compatible with linear secret sharing scheme. By incorporating the
techniques of linear secret sharing with any general access structure into the
Fourier-based FSS schemes, we show Fourier-based FSS schemes with any general
access structure.Comment: 12 page
Optimal non-perfect uniform secret sharing schemes
A secret sharing scheme is non-perfect if some subsets of participants that cannot recover the secret value have partial information about it. The information ratio of a secret sharing scheme is the ratio between the maximum length of the shares and the length of the secret. This work is dedicated to the search of bounds on the information ratio of non-perfect secret sharing schemes. To this end, we extend the known connections between polymatroids and perfect secret sharing schemes to the non-perfect case. In order to study non-perfect secret sharing schemes in all generality, we describe their structure through their access function, a real function that measures the amount of information that every subset of participants obtains about the secret value. We prove that there exists a secret sharing scheme for every access function. Uniform access functions, that is, the ones whose values depend only on the number of participants, generalize the threshold access structures. Our main result is to determine the optimal information ratio of the uniform access functions. Moreover, we present a construction of linear secret sharing schemes with optimal information ratio for the rational uniform access functions.Peer ReviewedPostprint (author's final draft
Economical (k,m)-threshold controlled quantum teleportation
We study a (k,m)-threshold controlling scheme for controlled quantum
teleportation. A standard polynomial coding over GF(p) with prime p > m-1 needs
to distribute a d-dimensional qudit with d >= p to each controller for this
purpose. We propose a scheme using m qubits (two-dimensional qudits) for the
controllers' portion, following a discussion on the benefit of a quantum
control in comparison to a classical control of a quantum teleportation.Comment: 11 pages, 2 figures, v2: minor revision, discussions improved, an
equation corrected in procedure (A) of section 4.3, v3: major revision,
protocols extended, citations added, v4: minor grammatical revision, v5:
minor revision, discussions extende
Lower Bounds for Monotone Span Programs
The model of span programs is a linear algebraic model of computation. Lower bounds for span programs imply lower bounds for contact schemes, symmetric branching programs and for formula size. Monotone span programs correspond also to linear secret-sharing schemes. We present a new technique for proving lower bounds for monotone span programs. The main result proved here yields quadratic lower bounds for the size of monotone span programs, improving on the largest previously known bounds for explicit functions. The bound is asymptotically tight for the function corresponding to a class of 4-cliques
Mitigating Misinformation Spreading in Social Networks Via Edge Blocking
The wide adoption of social media platforms has brought about numerous
benefits for communication and information sharing. However, it has also led to
the rapid spread of misinformation, causing significant harm to individuals,
communities, and society at large. Consequently, there has been a growing
interest in devising efficient and effective strategies to contain the spread
of misinformation. One popular countermeasure is blocking edges in the
underlying network.
We model the spread of misinformation using the classical Independent Cascade
model and study the problem of minimizing the spread by blocking a given number
of edges. We prove that this problem is computationally hard, but we propose an
intuitive community-based algorithm, which aims to detect well-connected
communities in the network and disconnect the inter-community edges. Our
experiments on various real-world social networks demonstrate that the proposed
algorithm significantly outperforms the prior methods, which mostly rely on
centrality measures