1 Introduction
A dealer wants to store a string of secret information (a.k.a. a secret) on a set of computers such that only some pre-defined subsets of the computers can reconstruct the information. We will refer to the computers as the parties, their number as n, and the collection of authorized sets that can reconstruct the secret as an access structure. To achieve this goal the dealer uses a secret-sharing scheme – a randomized function that is applied to the secret and produces n strings, called shares. The dealer gives the i-th share to the i-th party, and any authorized set of parties can reconstruct the secret from its shares. Nowadays, secret-sharing schemes are used as a building box in many cryptographic tasks (see, e.g., [10, 13]). We consider schemes where unauthorized sets of parties gain absolutely no information on the secret from their shares, i.e., the security is information theoretic. We will mainly try to reduce the sizes of the shares given to the parties. To understand why minimizing the share size is important, let us consider the original secret-sharing schemes of [44] for an arbitrary access structure; in these schemes the size of each share is greater than , making them impractical when, for example,
. Even in the most efficient scheme known today, the share size is
[5] (improving on [4, 48]).
We ask the question if the above share size can be reduced for almost all access structures. One motivation for this question is that in complexity theory, almost all Boolean functions are often the hardest functions. For example, Shannon [58] showed that almost all Boolean functions require circuits of size , this lower bound applies also to other models, e.g., formulas. Furthermore, almost all monotone Boolean functions require monotone circuits and monotone formulas of size
. Dealing with properties of almost all objects is a common theme in combinatorics, e.g., properties of almost all graphs. A famous example states that the size of the maximum independent set (and clique) of almost all n-vertex graphs is approximately
[43]; we use this property in our constructions. Using a result on almost all monotone Boolean functions [47], we show that almost all access structures can be realized by a secret-sharing scheme with maximum share size
.
In this paper, we also study graph secret-sharing schemes. In a secret-sharing scheme realizing a graph G, the parties are vertices of the graph G and a set can reconstruct the secret if and only if it contains an edge. The naive scheme to realize a graph is to share the secret independently for each edge; this result implies a share of size O(n) per party. A better scheme with share size per party is implied by a result of Erdös and Pyber [38]. Graph secret-sharing schemes were studied in many previous works. One motivation for studying graph secret-sharing schemes is that they are simpler than secret-sharing schemes for general access structures and phenomena proved for graph secret-sharing schemes were later generalized to general access structures (e.g., Blundo et al. [26] proved that in any non-ideal access structure the share size of at least one party is at least 1.5 times the size of the secret, a result that was later proved for every access structure [51]). Another motivation is that, by [54, Section 6.3.1], for every
any graph secret-sharing scheme with share size
per party implies a secret-sharing scheme for any access structure with share size
; thus, major improvement in the share size for all graphs will result in improved schemes for all access structures. However, in spite of the recent improvements in the share size for general access structures [4, 5, 48] and for specific families of access structures (e.g., forbidden graphs [18, 41, 49] and uniform access structures [2, 4, 19]), no such improvement was achieved for schemes for graphs. We show that almost all graphs can be realized by a secret-sharing scheme with share size
per party.
1.1 Previous Results

A summary of the upper and lower bounds on the maximum share size for secret-sharing schemes for forbidden graph access structures, almost all graph access structures, graph access structures, almost all access structures, and all access structures. The results proved in this paper are in boldface.
Measures of Share Size. The size of a share is simply the length of the string representing it. For a secret-sharing scheme, two measures of for the share size were considered: (1) the maximum share size, i.e., the maximum over all parties in the scheme of the size of the share of the party, (2) the total share size, i.e., the sum over all parties in the scheme of the size of the share of the party. For a given scheme, the maximum share size is bounded from above by the total share size, which is bounded from above by n times the maximum share size. The distinction between these two measures is important for graph secret-sharing schemes, and there might be trade-offs between optimizing one measure and optimizing the other. On the other hand, the share size in the secret-sharing schemes considered in this paper for general access structures is larger than , thus for these schemes the distinction between the measures is less important.
We will also consider the normalized total (respectively, maximum) share size, i.e., the ratio between the sum of the share sizes (respectively, maximum share size) and the size of the secret. This normalized maximum share size (also known as information ratio) is similar in spirit to measures considered in information theory and it is interesting since the length of each share is at least the length of the secret [46]. In this work, we will consider the normalized share size for two regimes: (1) Moderately short secrets of size , and (2) Following [2, 3], we also consider exponentially long secrets of size
. The latter size is not reasonable, however, these schemes may lead to schemes with the same share size for shorter secrets and they provide barriers for proving lower bounds via information inequalities.
Bounds on the Share Size. Secret-sharing schemes were introduced by Blakely [24] and Shamir [57] for the threshold case and by Ito, Saito, and Nishizeki [44] for the general case. In the original secret-sharing schemes for arbitrary access structures of Ito et al. [44] the maximum share size is . Additional constructions of secret-sharing schemes followed, e.g., [22, 23, 29, 45, 59]. For specific access structures, the share size in these schemes is less than the share size in the scheme of [44]; however, the share size in the above schemes for arbitrary access structures is
. In a recent breakthrough work, Liu, and Vaikuntanathan [48] (using results of [50]) constructed a secret-sharing scheme for arbitrary access structures with share size
and a linear secret-sharing scheme with share size
. Applebaum et al. [5] (using results of [4, 50]) improved these results, constructing a secret-sharing schemes for arbitrary access structures with share size
and a linear secret-sharing scheme with share size
. It is an important open problem if the share size can be improved to
(or even smaller). Lower bounds for secret-sharing were proven in, e.g., [25, 30, 33, 34, 37]. These lower bounds are very far from the upper bounds – the best lower bound is
for the normalized total share size for an explicit access structure (proven by Csirmaz [33]).
For graph secret-sharing schemes there is also a big gap between the upper bounds and lower bounds. Erdös and Pyber [38] have proved that every graph can be partitioned into complete bipartite graphs such that each vertex is contained in at most complete bipartite graphs. Blundo et al. [25] observed that this implies that the normalized maximum share size of realizing every n-vertex graph is
(for secrets of size
). Van Dijk [37] proved a lower bound of
on the normalized maximum share size of realizing an explicit n-vertex graph. Csirmaz [35] extended this lower bound to the n-vertex Boolean cube. He observed that a lower bound of
on a specific graph implies a lower bound of
for almost all graphs (as almost all n-vertex graphs contain a copy of every
-vertex graph [28]). Furthermore, Csirmaz asked if for almost every graph there is a scheme with normalized maximum share size
. We answer this question affirmatively by showing for almost all graphs a secret-sharing scheme with maximum share size
.
Linear Secret-Sharing Schemes. Linear secret-sharing schemes, introduced by [29, 45], are schemes in which the random string is a vector of elements over some finite field , the domain of secrets is also
, and the shares are computed as a linear map over
. Many known schemes are linear, e.g., [22, 24, 57] and the schemes for graphs implied by [38]. They are equivalent to a linear-algebraic model of computation called monotone span programs [45]. Linear secret-sharing schemes are useful as they are homomorphic: given shares of two secrets
, each party can locally add its shares and obtain a share of
. For many applications of secret sharing, linearity is essential, e.g., [8, 32, 61], hence, constructing linear secret-sharing schemes is important. The size of the shares in the best known linear secret-sharing scheme is
[5] (improving upon [48]). Pitassi and Robere [55] proved an exponential lower bound of
on the share in linear secret-sharing schemes over
for an explicit access structure of (where
is a constant). Babai et al. [9] proved a lower bound of
on the share in linear secret-sharing schemes over
for almost all access structures.
Multi-linear secret-sharing schemes, introduced by [23], are a generalization of linear secret-sharing schemes in which the domain of secrets is for some integer
. In [2, 5], such schemes improve the normalized maximum share size compared to the linear secret-sharing schemes constructed in those papers (i.e., the multi-linear schemes share a longer secret while using the same share size as the linear schemes). Beimel et al. [11] proved that every lower bound proved for linear secret-sharing schemes using the Gal-Pudlák criteria [40] also applies to multi-linear secret-sharing schemes. In particular, this implies that the
lower bound of [9] for the normalized maximum share size for an explicit access structure and the
lower bound of [17] for the normalized maximum share size for an explicit graph access structure hold also for multi-linear secret-sharing schemes. We note that it is not clear if multi-linear secret-sharing schemes can replace linear secret-sharing schemes in many applications, e.g., in the MPC protocols of [32] that are secure against general adversarial structures.
Conditional Disclosure of Secrets (CDS) Protocols [42]. A CDS protocol for a Boolean function f involves k servers and a referee. Each server holds a common secret s, a common random string r, and a private input ; using these r, s, and
the i-th server computes one message (without seeing any other input or message) and sends it to the referee. The referee, knowing the inputs
and the messages, should be able to compute s iff
. CDS protocols were used in many cryptographic applications, such as symmetric private information retrieval protocols [42], attribute based encryption [8, 41, 61], priced oblivious transfer [1], and secret-sharing schemes [4, 5, 48]. Applebaum et al. [5] defined robust CDS protocols (see Definition 2.10) and used them to construct secret-sharing schemes for arbitrary access structures. We use robust CDS protocols to construct schemes for almost all graphs and for all very dense graphs.
The original construction of k-server CDS protocols for general k-input functions, presented in [42], has message size (where N is the input domain size of each server). This construction is linear. Recently, better constructions of CDS protocols for general functions have been presented. Beimel et al. [18] have shown a non-linear 2-server CDS protocol with message size
and Gay et al. [41] constructed a linear 2-server CDS protocol with the same message size. Then, Liu et al. [49] have designed a 2-server non-linear CDS protocol with message size
and Liu et al. [50] have constructed a k-server CDS protocol with message size
. Beimel and Peter [20] and Liu et al. [50] have constructed a linear CDS protocol with message size
; by [20], this bound is optimal for linear CDS protocols (up to a factor of k). Applebaum and Arkis [2] (improving on Applebaum et al. [3]) have showed that there is a CDS protocol with long secrets – of size
– in which the message size is 4 times the secret size. Lower bounds on the message size in CDS protocols and in linear CDS protocols have been proven in [3, 6, 7, 41].
Forbidden Graph Access Structures. In a forbidden-graph secret-sharing scheme for a graph G, introduced by Sun and Shieh [60], the parties are the vertices of the graph G and a set is authorized if it is an edge or its size is at least 3. A forbidden-graph secret-sharing scheme for a graph G is not harder than a graph secret-sharing realizing G: Given a secret-sharing scheme realizing a graph, one can construct a forbidden-graph secret-sharing scheme for G by giving a share of the graph secret-sharing scheme and a share of a 3-out-of-n threshold secret-sharing schemes. Furthermore, forbidden graph secret-sharing schemes are closely related to 2-server CDS protocols: Beimel et al. [18] have described a transformation from a CDS protocol for a function describing the graph G to a forbidden graph secret-sharing scheme for G in which the maximum share size of the scheme is times the message size of the CDS protocol. Furthermore, by [2, 18], if we consider secrets of size at least
, then there is a transformation in which the normalized maximum share size is a constant times the message size of the CDS protocol. As a result, we get that every forbidden graph G can be realized by a secret-sharing with maximum share size
(using the CDS protocol of [49]), by a linear secret-sharing scheme over
with maximum share size
for every prime power q (using the CDS protocol of [41]), and a multi-linear secret-sharing scheme with normalized maximum share size O(1) for secrets of length
[2]. We nearly match these bounds for graph access structures for almost all graphs.
1.2 Our Results and Techniques
We next describe the results we achieve in this paper. We again refer the reader to Fig. 1 for a description of the maximum share size in previous constructions and our constructions.
Almost All Access Structures. We prove upper bounds on the share size for almost all access structures, namely almost all access structures have a secret-sharing scheme with share size , a linear secret-sharing scheme with share size
, and a multi-linear secret-sharing scheme with maximum share size
for secrets of size
. Our linear secret-sharing scheme for almost all access structures are optimal (up to a factor of
) for a one-bit secret (by a lower bound of Babai et al. [9]).
The construction for almost all access structures is a simple combination of previous results. The first result, proved by Korshunov [47] in 1981, is that in almost all access structures with n parties all minimum authorized sets are of size between and
, i.e., all sets of size at most
are unauthorized and all sets of size at least
are authorized. The second result we use, proved by Liu and Vaikuntanathan [48], is that such access structures can be realized by secret-sharing schemes with share size as above. These results are presented in Sect. 3.
We also prove lower bounds on the normalized share size in linear secret-sharing schemes for almost all access structures. Rónyai et al. [56] proved that for every finite field for almost all access structures the normalized share size of linear secret-sharing schemes over
realizing the access structure is at least
. The result of Rónyai et al. [56] does not rule-out the possibility that for every access structures there exists some finite field
(possibly with a large q) such that the access structure can be realized by a linear secret-sharing schemes over
with small normalized share size. This could be plausible since we know that there are access structures that can be realized by an efficient linear secret-sharing scheme over one field, but require large shares in any linear secret-sharing scheme over fields with a different characteristic [21, 55]. Pitassi and Robere [55] proved that there exists an explicit access structure for which this is not true, i.e., there exists a constant
such that in any linear secret-sharing scheme realizing it the normalized share size is
. In Theorem 3.10, we prove that this is not true for almost all access structures, namely, for almost every access structure the normalized share size in any linear secret-sharing scheme realizing the access structure is
. Our proof uses a fairly recent result on the number of representable matroids [53].
(G, t)-Graph Secret-Sharing Schemes and Robust CDS. We define a hierarchy of access structures between forbidden graph access structures and graph access structures. In a (G, t)-secret-sharing scheme, every set containing an edge is authorized and, in addition, every set of size is authorized. In other words, the unauthorized sets are independent sets in G of size at most t. We show that (G, t)-secret-sharing schemes are equivalent to 2-server t-robust CDS protocols. As a result, using the robust CDS protocols of [5], we get efficient (G, t)-secret-sharing schemes, e.g., schemes with maximum share size
. These results are presented in Sect. 4. We note that, for an arbitrary graph G, our (G, n)-secret-sharing scheme, which is a graph secret-sharing scheme realizing G, the share size does not improve upon the scheme of [38].
Almost All Graph Secret-Sharing Schemes. We show that for almost all graphs, there exists a secret-sharing scheme with maximum share size , a linear secret-sharing scheme with normalized maximum share size
(for moderately short secrets), and a multi-linear secret-sharing scheme with normalized maximum share size
for exponentially long secrets. By [11, 17], there exists a graph such that in every multi-linear secret-sharing scheme realizing the graph the normalized maximum share size is
, thus, we get a separation for multi-linear secret-sharing schemes between the normalized maximum share size for almost all graphs and the maximum share size of the worst graph. These results are presented in Sect. 5.
To construct our scheme for almost all graphs, we use the fact that if the size of every independent set in a graph G is at most t, then a (G, t)-secret-sharing scheme is a graph secret-sharing scheme realizing G. Our construction follows from the fact that for almost every graph, the size of the maximal independent set in a random graph is [43].
We also consider the maximum share size of random n-vertex graphs drawn from the Erdös-Rényi [39] distribution , that is, each pair of vertices is independently connected by an edge with probability p. For example,
is the uniform distribution over the n-vertex graphs. On one hand, with probability nearly 1 the size of the maximum independent set in a graph drawn from
is at most
, thus, using (G, t)-secret-sharing schemes with
, we realize a graph in
with normalized maximum share size
. On the other hand, with probability nearly 1 the degree of all vertices in the graph drawn from
is O(pn), thus, it can be realized by the trivial secret-sharing scheme with maximum share size O(pn). Combining these two schemes, the hardest distribution in our construction is
for which the normalized maximum share size is
. We do not know if there is a better secret-sharing scheme for graphs drawn from
or this distribution really requires shares of size
.
Dense Graph Secret-Sharing Schemes. Following [14], we study graph secret-sharing schemes for very dense graphs, i.e., graphs with at least edges for some constant
. For these graphs, Beimel et al. [14] have constructed a linear secret-sharing scheme with maximum share size
and another linear secret-sharing scheme with total share size
. We improve on the latter result and show that all very dense graphs can be realized by a secret-sharing scheme with normalized total share size of
for moderately short secrets of size
. To put this result in perspective, this total share size matches (up to a factor of
) to the total share size of the naive secret-sharing scheme for sparse graphs with
edges. These schemes are presented in Sect. 6.
We next describe the high-level ideas of our construction realizing a graph G with at least edges. If every vertex in G has degree at least
, then the size of every independent set in G is at most
, and we can use a
-secret-sharing schemes, resulting in normalized total share size
. While in a graph with at least
edges the average degree is at least
, the graph can contain vertices whose degree is small. To overcome this problem, we use an idea of [14]. We consider the set of vertices A whose degree is smallest in G and execute a secret-sharing scheme realizing the graph restricted to this set (denoted
). We choose the size of this set such that: (1) the size of the set is small, thus, the total share size in realizing
is small, and (2) the degree of the each vertex not in A is big, thus, we can realize the graph without the edges between vertices in A by a (G, t)-secret-sharing scheme for a relatively small t. We apply the above construction iteratively to get our scheme.
Hypergraph Secret-Sharing Schemes. A secret-sharing realizes a hypergraph H if the parties of the scheme are the vertices of H and a set of parties can reconstruct the secret if and only if it contains a hyperedge. In this work, we construct schemes for k-hypergraphs, that is, hypergraphs whose hyperedges are all of size k. The access structures of these schemes are also called k-homogeneous. The best secret-sharing scheme for k-hypergraphs known to date is the original scheme of [44], which have maximum share size . Extending the results explained above, we show a connection between k-hypergraph secret-sharing schemes and k-server t-robust CDS protocols. For any constant k, we show that for almost every k-hypergraph there exists a secret-sharing scheme with maximum share size is
, a linear secret-sharing scheme with normalized maximum share size
, and a multi-linear secret-sharing scheme with normalized maximum share size
for exponentially long secrets. These schemes are presented in the full version of this paper [13].
Interpretation of Our Results. In this work we have shown that for almost all access structures there exist secret-sharing schemes that are more efficient than the known secret-sharing schemes for the worst access structures. Similarly, we have constructed for almost every graph G a secret-sharing schemes realizing G that are more efficient than the known secret-sharing schemes realizing the worst graph. One possible conclusion from this result is that in secret-sharing schemes almost all access structures might not be the hardest access structures. Another possible interpretation is that our results may be generalized to all access structures. We note that in one case we know that the former interpretation is true: there is a graph for which the normalized maximum share size for multi-linear schemes is at least (for every size of secrets) [11, 17], while we show an upper bound for almost all graphs of
(for long secrets).
Open Problems. Can the normalized share size of almost all access structures can be improved? We do not have any non-trivial lower-bound on the normalized share size for them. Recall that an access structure is n/2-uniform if all sets of size less than n/2 are unauthorized, all sets of size greater than n/2 are authorized, and sets of size exactly n/2 can be either authorized or unauthorized. By [4] (using results of [2]), every n/2-uniform access structure can be realized by a scheme with normalized maximum share size (with exponentially long secrets). Since almost all access structures somewhat resemble uniform access structures (see Theorem 3.2), one can hope that almost every access structure can be realized by a scheme with polynomial normalized share size.
Another research problem is to study the complexity of almost all functions for other primitives with information-theoretic security, for example, private simultaneous messages (PSM) protocols, MPC protocols, MPC protocols with constant number of rounds, and private information retrieval (PIR) protocols for almost all databases. For all these primitives there is a huge gap between the known upper bounds and lower bounds on the message size. Are there more efficient protocols for any of these primitives for almost all functions than the protocols for all functions?
2 Preliminaries
In the section, we present the preliminary results needed for this work. First, we define secret-sharing schemes, linear secret-sharing schemes, graph secret-sharing schemes, and homogeneous access structures. Second, we define conditional disclosure of secrets (CDS) protocols, and robust CDS protocols. We also present several CDS and robust CDS protocols from [2, 20, 49, 50] that are used in this work. Finally, we present a short introduction to random graphs and random access structures.
Secret-Sharing Schemes. We present the definition of secret-sharing scheme as given in [12, 31]. For more information about this definition and secret-sharing in general, see [10].
(Access Structures). Let be a set of parties. A collection
is monotone if
and
imply that
. An access structure is a monotone collection
of non-empty subsets of
. Sets in
are called authorized, and sets not in
are called forbidden.
(Secret-Sharing Schemes). A secret-sharing scheme with domain of secrets S, such that
, is a mapping from
, where R is some finite set called the set of random strings, to a set of n-tuples
, where
is called the domain of shares of
. A dealer distributes a secret
according to
by first sampling a random string
with uniform distribution, computing a vector of shares
, and privately communicating each share
to party
. For a set
, we denote
as the restriction of
to its A-entries (i.e., the shares of the parties in A).
A secret-sharing scheme with domain of secrets S realizes an access structure
if the following two requirements hold:
Correctness. The secret s can be reconstructed by any authorized set of parties. That is, for any set there exists a reconstruction function
such that
for every secret
and every random string
.
Privacy. Any forbidden set cannot learn anything about the secret from its shares. Formally, for any set and every pair of secrets
, the distributions
and
are identical, where the distributions are over the choice of r from R at random with uniform distribution.
Given a secret-sharing scheme , define the size of the secret as
, the share size of party
as
, the maximum share size as
, and the total share size as
.
A secret-sharing scheme is multi-linear if the mapping that the dealer uses to generate the shares given to the parties is linear, as we formalize at the following definition.
(Multi-linear and Linear Secret-Sharing Schemes). Let be a secret-sharing scheme with domain of secrets S. We say that
is a multi-linear secret-sharing scheme over a finite field
if there are integers
such that
,
,
, and the mapping
is a linear mapping over
from
to
. We say that a scheme is linear over
if
(i.e., when
).
(Graph secret-sharing schemes). Let be an undirected graph with
; for simplicity we assume that
. We define
as the access structure whose minimal authorized subsets are the edges in G, that is, the unauthorized sets are independent sets in the graph. A secret-sharing scheme realizing an access structure
is said to be a secret-sharing scheme realizing the graph G and is called a graph secret-sharing schemes.
These schemes are one of the main topics in this work. In this paper, we study very dense graphs, graphs with at least edges for some
.
We also study k-homogeneous access structures, which are access structures whose minimal authorized subsets are of the size k. For example, graph access structures are 2-homogeneous access structures. For , it is convenient to define k-homogeneous access structures from hypergraphs. A hypergraph is a pair
where V is a set of vertices and
is the set of hyperedges. A hypergraph is k-uniform if
for every
. A k-uniform hypergraph is complete if
. Observe that there is a one-to-one correspondence between uniform hypergraphs and homogeneous access structures, and that complete uniform hypergraphs correspond to threshold access structures. Given a hypergraph
, we define
as the access structure whose minimal authorized sets are the hyperedges of H.
We contrast homogeneous access structures with uniform access structures (studied, e.g., in [2, 4, 19, 60]). A k-uniform access structures is also described by a k-uniform hyper-graph and its authorized sets are all the hyper-edges and all sets of size at least . Thus, k-homogeneous access structures are harder to realize as they might contain forbidden sets of size much larger than k.1
Conditional Disclosure of Secrets. We define k-server conditional disclosure of secrets protocols, originally defined in [42].


- 1.
A finite domain of common random strings R, and k finite message domains
,
- 2.
Deterministic message computation functions
, where
for every
(we also say that
is the message sent by the i-th server to the referee), and
- 3.
A deterministic reconstruction function
.
We denote . We say that a CDS protocol
is a CDS protocol for a function f if the following two requirements hold:










The message size of a CDS protocol is defined as the size of largest message sent by the servers, i.e.,
.
Next, we present the properties of three CDS protocols that are used in this work. The CDS protocol presented in Theorem 2.6 has linear properties: the messages are generated from the secret and the randomness with linear mappings. Theorem 2.6 is a particular case of Theorem 6 of [2], while Theorem 2.7 is from [49].
([2]). For any 2-input function there is a 2-server CDS protocol in which, for sufficiently large secrets, i.e., secrets of size
, each server communicates at most 3 bits per each bit of the secret.
([49]). For any 2-input function there is a 2-server CDS protocol with a one bit secret and message size
.
([50]). For any k-input functions there is a k-server CDS protocol with a one bit secret and message size
.
Robust Conditional Disclosure of Secrets. In a recent work [5], Applebaum et al. define a stronger notion of CDS protocols that is useful for constructing secret-sharing schemes. In a k-server CDS protocol, we assume that each server sends one message to the referee. Therefore, the referee only has access to k messages. In a robust k-server CDS protocol, we consider the case that the referee can have access to more than one message from some servers (generated with the same common random string), and privacy is guaranteed even if an adversary sees a bounded number of messages from each server.







(Robust conditional disclosure of secrets (RCDS) protocols). Let be a k-server CDS protocol for a k-input function
and
be a zero set of f. We say that
is robust for the set Z if for every pair of secrets
, it holds that
and
are identically distributed. Let
be integers. We say that
is a
-robust CDS protocol if it is robust for every zero set
such that
for every
and it is a t-robust CDS protocol if it is
-robust.
In this work we use several constructions of robust CDS protocols presented in [4], which are based on non-robust CDS protocols. Theorem 2.11 presents linear and multi-linear robust CDS protocols in which the underlying CDS protocol is from [41]. Then, Theorem 2.12 presents a generic transformation from non-robust CDS protocols to robust CDS protocols. In this transformation, if the original CDS is linear, then the resulting robust CDS is multi-linear.
([5, Theorem D.5]). Let be a function. Then, for every finite field
and every integer
, there is a linear 2-server (t, N)-robust CDS protocol for f with one element secrets in which the message size is
Furthermore, there is
such that for every prime-power
there is a multi-linear 2-server (t, N)-robust CDS protocol for f over
with secrets of size
in which the normalized message size is
([5, Theorem E.2]). Let be a k-input function, for some integer
, and
be an integer. Assume that for some integer
, there is a k-server CDS protocol
for f with secrets of size m in which the message size is c(N, m). Then, there is a k-server t-robust CDS protocol for f with secrets of size m in which the message size is
If
is a linear protocol over
, then the resulting protocol is also linear. Furthermore, there is a k-server t-robust CDS protocol for f with secrets of size
in which the normalized message size is
Random Graphs and Access Structures. In this work, we use several results on random graphs to construct secret-sharing schemes for almost all graphs with improved share size. First, we present the Erdös-Rényi model for random graphs [39]. For an introduction to this topic see, e.g., [27].
Let be the family of graphs with the vertex set
. Given
, the model
is a probability distribution over
in which each edge is chosen independently with probability p, that is, if G is a graph with m edges, then
Note that when
, any two graphs are equiprobable.
We say that almost every graph in has a certain property Q if
as
. For
, saying that almost every graph in
has a certain property Q is equivalent to saying that the number of graphs in
satisfying Q divided by
tends to 1 as
. In this case, we will say that almost all graphs satisfy Q.
Analogously, we will use the same expression for any family of access structures . We say that almost all access structures in
satisfy Q if the number of access structures in
satisfying Q divided by
tends to 1 as
. In particular, we study the family of homogeneous access structures and the family of all access structures.
Next, we present some properties of the maximum independent sets of graphs in . Lemma 2.13 was presented by Grimmett and McDiarmid in [43]. Several subsequent results gave more accurate bound on the size of maximum independent sets, but it is enough for our purposes. In Lemma 2.14 we give bounds to the maximum independent sets in
for non-constant p. In Lemma 2.15 and Lemma 2.16 we present further properties of almost all graphs. The proofs of Lemmas 2.14 and 2.15 are in the full version of this paper [13].
([43]). Let be a constant. Then the size of a maximum independent set in almost every graph in
is smaller than
.
As a consequence of Lemma 2.13, the size of a maximum independent set in almost every graph in is smaller than
.
The size of a maximum independent set in almost every graph in is
if
, and
if
for some
.
With a similar proof, we can also show that for every , almost all graph with
edges have maximal independent sets of size at most
, and almost all graphs with
have maximal independent sets of size at most
.
Almost all graphs in with
have degree at most 2pn.
([28, Theorem 1]). Almost every graph with vertices contains every graph of r vertices as an induced subgraph.
3 Secret-Sharing Schemes for Almost All Access Structures
This section is dedicated to the study of general access structures. Combining results on monotone Boolean functions by Korshunov [47] and secret-sharing schemes from [2, 48], we obtain secret-sharing schemes for almost all access structures. Then, we present lower bounds on the maximum share size for almost all access structures.
3.1 Upper Bounds for Almost All Access Structures
First, we define the family of slice access structures. These access structures have a special role in the general constructions presented in [4, 5, 48]. In Theorem 3.2, we present a family of slice access structures that contains almost all access structures. It is direct consequence of the results in [47] for monotone Boolean functions (also presented in [62, p. 99]).
Let a, b be two integers satisfying . We define
as the family of access structures
satisfying that, for every
: if
, then
, and if
, then
.
([47]). Let . Almost all access structures (i.e., monotone collections of sets) are in
if n is even, and in
if n is odd.
Almost all access structures can be realized by the following secret-sharing schemes.
- 1.
A secret-sharing scheme with maximum share size
.
- 2.
A linear secret-sharing scheme with maximum share size
.
- 3.
A multi-linear secret-sharing scheme with normalized maximum share size
for secrets of size
.
By Theorem 3.2, constructing secret-sharing schemes for access structures in suffices for constructing secret-sharing schemes for almost all access structures.
![$$f : [N]^k\rightarrow \{0,1\}$$](../images/508076_1_En_18_Chapter/508076_1_En_18_Chapter_TeX_IEq325.png)











As a consequence of this result, Hypotheses 1 and 3 in [2] are true for almost all access structures:
(SS is short). Every access structure over n parties is realizable with small information ratio (say ).
(SS is amortizable). For every access structure over n parties, and every sufficiently long secret s, there exists a secret-sharing scheme with small information ratio (e.g., sub-exponential in n).
3.2 Almost All Access Structures Require Long Shares in Linear Secret-Sharing Schemes
Rónyai et al. [56] proved that for every finite field for almost every access structure
the normalized total share size of linear secret-sharing schemes over
realizing
is at least
. We reverse the order of quantifiers and prove that for almost every access structure
, for every finite field
the normalized total share size of linear secret-sharing schemes over
realizing
is at least
.
The rest of the section is organized as follows. We start by defining monotone span program and representable matroids; these notions are used to prove the lower bounds. Thereafter, we prove our new lower bound on the normalized total share size of linear secret-sharing schemes. More details about these results can be found in [13].
Definitions. A linear secret-sharing scheme with total share size m can be described by a matrix M with m rows such that the shares are computed by multiplying M by a vector whose first coordinate is the secret s and the other coordinates are random field elements. It is convenient to describe a linear secret-sharing scheme by a monotone span program, a computational model introduced by Karchmer and Wigderson [45]. The reader is referred to [10] for more background on monotone span programs and their connections to secret sharing.
(Monotone Span Program [45]). A monotone span program is a triple , where
is a field, M is an
matrix over
, and
labels each row of M by a party.2 The size of
is the number of rows of M (i.e.,
). For any set
, let
denote the sub-matrix obtained by restricting M to the rows labeled by parties in A. We say that
accepts B if the rows of
span the vector
. We say that
accepts an access structure
if
accepts a set B if and only if
.
([45]). There exists a linear secret-sharing scheme over realizing an access structure
with secrets of size
and total share size
if and only if there exists a monotone span program
accepting the access structure
such that M is an
matrix.
We next define representable matroids and quote the result of [53]. For our proof, we do not need the definition of matroids; we note that they are an axiomatic abstraction of linear independency.







([53]). For every , there are at most
representable matroids with ground set [d].
The following theorem generalize the lower bounds of [9, 56].
For almost every access structure with n parties the following property holds: For every prime-power q, the normalized total share size in every linear secret-sharing scheme realizing
over the field
is at least
.
The proof is similar to the proof of [9], with a more complex upper bound on the number of access structure that can be realized with a monotone span program of size .
![$$\rho _0:[d] \rightarrow \left\{ p_1,\dots ,p_n \right\} $$](../images/508076_1_En_18_Chapter/508076_1_En_18_Chapter_TeX_IEq384.png)




















A Lower Bound on the Share Size in Linear Secret-Sharing Schemes with a One Bit Secret. Finally, for a one-bit secret, we obtain in Theorem 3.11 a lower bound of on the total share size of linear secret-sharing schemes over any field realizing almost all access structures, even if the secret is a bit. Notice that this lower bound is on the total share size (and not on the normalized total share size). When we share a bit using a linear secret-sharing scheme over
for
, we only use the scheme to share the secrets
. Since we are proving a lower bound the total share size, assuming that the secret is a bit only makes the result stronger.
The constant in the exponent in Theorem 3.11 is 1/2 (compared to a constant 1/3 in Theorem 3.10), matching the construction of linear secret-sharing schemes for almost all access structures in Theorem 3.3 (up to lower order terms). This theorem is a special case of [4, Theorem 5.5], however, the proof of this special case is simpler.
For almost every access structure with n parties the following property holds: For every prime-power q, the total share size in every linear secret-sharing scheme over
realizing
with a one bit secret is at least
.


















4
-Secret-Sharing Schemes
In this section, we present a new family of schemes that we call (G, t)-secret-sharing schemes. We show that there is a close bi-directional connection between these schemes and 2-server robust CDS protocols, generalizing the connection between (non-robust) CDS protocols and forbidden graphs secret-sharing schemes. These schemes will be later used to construct graph secret-sharing schemes.
4.1 The Definition of
-Secret-Sharing Schemes
Let be an undirected graph with
such that
and let
be the graph access structure determined by G (that is, each edge is a minimal authorized set and each independent set is forbidden). For any
, define
as the t-out-of-n threshold access structure on V (that is,
) and define the access structure
on V as
We say a secret-sharing scheme is a (G, t)-secret-sharing scheme if it realizes the access structure
.
Next, we present some properties of these schemes. If is a (G, t)-secret-sharing scheme, then all subsets containing edges are authorized, independent subsets of G of size at most t are forbidden, and subsets of size greater than t are authorized. If
, then
is a forbidden graph access structure determined by a graph G (for an introduction to these access structures, see [16], for example). If the size of a largest independent set of G is
, then every subset of size
is authorized in
. Therefore,
for every
. In particular,
for every graph G.
4.2
-Secret-Sharing Schemes from Robust CDS Protocols
We now present constructions of (G, t)-secret-sharing schemes. First, we present a transformation from robust CDS protocols to (G, t)-secret-sharing schemes. Then, using the robust CDS schemes presented in Sect. 2, we provide explicit (G, t)-secret-sharing schemes.
Let be a graph with
, and let
. If there exists a 2-server t-robust CDS protocol with secrets of size m and messages of size c(N, m) for functions
, then there is a (G, t)-secret-sharing scheme with secrets of size m and shares of size
. Moreover, if CDS protocol is linear, then the secret-sharing scheme is also linear.
We construct the (G, t)-secret-sharing scheme using the scheme in Fig. 2. Next we prove the correctness and privacy properties.
Correctness: Let be a minimal authorized subset in
. Then A is either in E or A is of size
. If
is in E, then
, i.e., the message of Alice (the first server) on i and the message of Bob (the second server) on j determines s, so the pair
can recover s. If
, then A can recover s using the
-out-of-n secret-sharing scheme.
Privacy: Let A be a maximal forbidden subset. Then A does not contain any edge in E and . The shares received from the threshold secret-sharing scheme do not provide any information about s. Now we analyze the information provided by the messages of
. The parties in A receive Alice’s messages for A and Bob’s messages for A. Observe that the set
does not contain edges of G, thus,
is a zero-set of f and the t-robustness of
guarantees the privacy of the scheme.
The maximum share size of the resulting scheme is twice the message size of plus the share size of the
-out-of-n secret-sharing scheme.
If is a linear protocol over
, we can choose a Shamir
-out-of-n secret-sharing scheme over a finite field
with
. Since this scheme is also linear over
, the resulting secret-sharing scheme is also linear over
.

A (G, t)-secret-sharing scheme for a graph
.
In Lemma 4.2, we showed a way to construct (G, t)-secret-sharing schemes from t-robust CDS protocols. Conversely, we can also construct robust CDS protocols from (G, t)-secret-sharing schemes, as shown in Lemma 4.3.
Let be a function and let
. Define
as the bipartite graph with
. If there exists a (G, 2t)-secret-sharing scheme with secrets of size m and maximum share size c(2n, m), then there exists a 2-server t-robust CDS protocol for f with message size c(2n, m).
Let be a (G, 2t)-secret-sharing scheme. We define a 2-server t-robust CDS protocol
for f as follows. The message spaces
and
of the servers are the spaces of shares of parties
and
, respectively. The common randomness r is the randomness of the dealer in
. The function
for
outputs the share of party (j, i) with the secret s and randomness r, and
is the reconstruction function of
.
The correctness of is guaranteed because every pair in E is authorized in
. The t-robustness of
is guaranteed because every zero-set
where
corresponds to an independent set
of size at most 2t in G, thus the messages of the inputs in
are shares of a forbidden set in
.
Now that we showed the connection between (G, t)-secret-sharing schemes from t-robust CDS protocols, we present (G, t)-secret-sharing schemes that use Theorems 2.12 and 2.11.
Let be a graph with
, and let
. If there exist a 2-server CDS protocol with message size c(N, m) for functions with domain size n and secrets of size m, then there exists a (G, t)-secret-sharing scheme with maximum share size
and a (G, t)-secret-sharing scheme with secrets of size
and normalized maximum share size
Theorem 2.12 guarantees that there exists a 2-server t-robust CDS protocol with message size and a 2-server t-robust CDS protocol with secrets of size
with normalized message size
Using these 2-server t-robust CDS protocols and Lemma 4.2 we obtain the lemma.
We conclude this section presenting different (G, t)-secret-sharing schemes that are obtained from robust CDS schemes applying Lemma 4.2 and Lemma 4.4.
Let be a graph with
and let
.
- 1.There exists a (G, t)-secret-sharing scheme with moderately-short secrets of size
, normalized maximum share size
and normalized total share size;
- 2.
For every prime power q, there exists a linear (G, t)-secret-sharing scheme over
with and maximum share size
- 3.
There exists an integer
such that for every prime power
, there exists a multi-linear (G, t)-secret-sharing scheme over
with moderately-short secrets of size
and normalized maximum share size
;
- 4.
There exists a multi-linear (G, t)-secret-sharing scheme over
with secrets of size
and normalized maximum share size
.
Scheme 1: By Theorem 2.7, for any function there exists a 2-server CDS protocol with secret of size
and messages size
. Applying Theorem 2.12 with the CDS protocol from Theorem 2.7 results in a 2-server t-robust CDS protocol with secrets of size
, message size
, and normalized message size
By Lemma 4.2, there is a (G, t)-secret-sharing with secrets of size
and maximum share size
, thus with normalized maximum share size
and with normalized total share size
.
Scheme 2: Theorem 2.11 guarantees that for there exists a linear 2-server t-robust CDS protocol over
with message size
. Thus, by Lemma 4.2 there is a (G, t)-secret-sharing scheme where the maximum share size is the above message size. For
, the upper bound also holds because there is always a linear (G, t)-secret-sharing with maximum share size
[38].
Scheme 3: Theorem 2.11 also guarantees, for a large enough q, a 2-server (t, n)-robust CDS protocol with secrets of size and normalized message size
. Again, we construct the desired (G, t)-secret-sharing with from the robust CDS protocol applying Lemma 4.2.
Scheme 4: By Theorem 2.6, there exists a multi-linear CDS protocol over with normalized message size
for secrets of size
. Applying Lemma 4.4, we obtain a multi-linear (G, t)-secret-sharing over
with normalized maximum share size
.
5 Secret-Sharing Schemes for Almost All Graphs
In this section we study the maximum share size of secret-sharing schemes for almost all graphs and for almost all graphs in for different values of p. The previous and new results for almost all graphs are summarized in Fig. 1, while the results for
are summarized in Fig. 4.
Schemes presented in this section rely on the properties of almost all graphs shown in the end of Sect. 2, and use the (G, t)-secret-sharing schemes presented in Sect. 4. In order to understand the share size of secret-sharing schemes for almost all graphs, we provide lower bounds for them in Theorems 5.5 and 5.7.
5.1 Schemes for Almost All Graphs
As a consequence of Lemma 2.13, the size of every independent set in almost every graph in is
. We observed in Sect. 4 that a (G, t)-secret-sharing scheme is also a secret-sharing scheme realizing G when t is bigger than the size of a largest independent set of G. Hence, we consider the four constructions presented in Theorem 4.5 for
. In Theorem 5.1 we present the resulting schemes.
Almost all graphs with n vertices can be realized by the following schemes.
- 1.
A secret-sharing scheme with maximum share size
,
- 2.
A linear secret-sharing scheme over
with maximum share size
for every prime power q,
- 3.
A multi-linear secret-sharing scheme over
with normalized maximum share size
and moderately-short secrets of size
for a large enough q, and
- 4.
A multi-linear secret-sharing scheme over
with normalized maximum share size
for secrets of size
.
5.2 Secret-Sharing Schemes for 
In order to study properties of sparse graphs, we study for a constant
. Almost all graphs in
have maximal independent sets of size at most
. Following the procedure we developed in the previous section, we can construct secret-sharing schemes for almost all graphs in
using Theorem 4.5. Similar bounds can be obtained for linear schemes and multi-linear schemes. They are presented in Fig. 4.
Let be a constant. Almost every graph in
can be realized by a secret-sharing scheme with normalized maximum share size
and secret of size
.
We present two schemes and
for almost all graphs in
. The scheme
consists on sharing the secret for each edge independently. By Lemma 2.15, almost every graph in
has maximum degree of at most
. Therefore, the maximum share size of
is
for almost all graphs in
.
The second scheme is obtained from Theorem 4.5. For almost every graph in
the size of a maximum independent set is
(by Lemma 2.14). Thus, we let
be the
-secret-sharing scheme of Theorem 4.5 with secret of size
and normalized maximum share size
.
Therefore, almost every graph in can be realized by a secret-sharing scheme with normalized maximum share size
.
For , the best choice is
, and for
, the best choice is
. For
, the normalized maximum share size of almost all graphs in
in our scheme is
. This is the constant
that gives the worst upper bound on the normalized maximum share size of secret-sharing schemes for
.
Finally, we study properties of very dense graphs by analyzing for a constant
. By Lemma 2.14, the size of a maximum independent set for almost all graphs in
is constant. As we saw above, graphs with small independent sets admit more efficient schemes. In Theorem 5.4 we present secret-sharing schemes for almost all graphs in
. Two of the schemes we present in Theorem 5.4 follow quite easily from our previous results. In contrast, the linear scheme we construct in Theorem 5.4 does not follow from previous results on robust CDS protocols. Rather, it follows from the following theorem of [16] on the total share size for forbidden graph secret sharing schemes and the techniques of [5].
([16, Theorem 6]). Let graph with n vertices and at least
edges, for some
. Then for every prime-power
there is a linear (G, 2)-secret-sharing scheme over
that with total share size
.
Let be a constant. Almost all graphs in
can be realized by a secret-sharing scheme with maximum share size
, a linear secret-sharing scheme over
with total share size
for every prime-power
, and a multi-linear secret-sharing scheme over
with exponentially long secrets of size
and normalized maximum share size O(1).
By Lemma 2.14, the size of a maximum independent set for almost all graphs in is some constant c. The non-linear secret-sharing scheme and the secret-sharing scheme with long secrets are obtained by applying Theorem 4.5 with
.




![$$\mathcal {H}=\left\{ h_i:[n]\rightarrow [c^2]: 1 \le i \le \ell \right\} $$](../images/508076_1_En_18_Chapter/508076_1_En_18_Chapter_TeX_IEq629.png)


Input: a secret
.
Choose
random elements
from
and let
.
For every
and every
, independently share
using the (G, 2)-secret-sharing scheme and give the share of vertex v to v if and only if
.
For the correctness of the scheme , let (u, v) be an edge in G (i.e., an authorized set). For every i, the parties u, v can reconstruct
from the scheme for
. For the privacy of
, let B be an independent set in G (i.e., a forbidden set). By Lemma 2.14, we can assume that the size of B is at most c, thus, there exists a hash function
such that
for every distinct
. Therefore, in any sharing of
for some values a, b the parties in B hold at most 2 shares, and these shares are of a forbidden set. The privacy of the (G, 2)-secret-sharing scheme implies that the parties in B do not get any information on
from this execution. Since all executions of the (G, 2)-secret-sharing scheme are executed with an independent random string, the parties in B do not get any information on
from the shares of
, hence they get no information on s. Note that the total share size in
is
times the total share size of the (G, 2)-secret-sharing scheme.
5.3 Lower Bounds for the Share Size for Almost All Graphs
Next, we present lower bounds for the maximum share size of secret-sharing schemes for almost all graphs. This question was first addressed by Csirmaz in [35], where he proved a lower bound which we include in Theorem 5.5.
For almost every graph G, the normalized maximum share size of every secret-sharing scheme realizing G is , and the normalized maximum share size of every multi-linear secret-sharing scheme realizing G is
.
(Sketch). Both bounds are a consequence of Lemma 2.16 (which says that almost all n-vertex graphs contain all graphs of size as an induced graph), taking different graphs with
vertices. The first bound was proved by Csirmaz in [35], taking the family of hypercube graphs (or the graphs of [37]). The second bound is a consequence of the results in [11, 17]. The complete proof is in the full version of this paper [13].
Lemma 2.16 provides a connection between the maximum share size of schemes for every graph access structure with vertices and the maximum share size of schemes for almost all graph access structures with n vertices. In Theorem 5.5 we used it in one direction, but it could also be used in the converse direction. For instance: if there exist secret-sharing schemes for almost all n-vertex graphs with (normalized) maximum share size
, then there exist secret-sharing schemes realizing every r-vertex graph with (normalized) maximum share size
, which is currently the best upper bound [38].
In Theorem 5.7, we quote a lower bound on the maximum share size for linear graph secret-sharing schemes, proved in [15, 52]. Notice, however, that this bound does not grow as a function of the size of the secrets.
6 Secret-Sharing Schemes for Very Dense Graphs
In this section we study secret-sharing schemes for very dense graphs, i.e., graphs with n vertices and at least edges for some
. This problem was originally studied in [14], and the best previously known upper bounds on the maximum share size and the total share size are presented in Theorems 6.1 and 6.2.
([14]). Let be a graph with
and
for some
. Then, there exists a linear secret-sharing scheme realizing G with maximum share size
, total share size
, and secret of size
.
The above theorem hides poly-logarithmic factors in the share size. It was also shown in [14] that these poly-logarithmic factors can be avoided if we consider multi-linear secret-sharing schemes and normalized share size: for the graphs considered in Theorem 6.1, there exists a multi-linear secret-sharing scheme with normalized maximum share size and secret of size
.
In [14], there is another secret-sharing construction for very dense graphs, presented in Theorem 6.2. The total share size of this scheme is smaller than the one in Theorem 6.1, but the maximum share size may be larger.
([14]). Let be a graph with
and
for some
. There exists a linear secret-sharing scheme realizing G with total share size
.
As an observation, notice that as a direct implication of the results in previous sections we can construct a scheme whose maximum share size is similar to the maximum share size as in the scheme of Theorem 6.2 (see the full version of this paper [13]).
We use (G, t)-secret-sharing schemes, described in the Sect. 4, to construct secret-sharing schemes for all very dense graphs. Our main result for dense graphs is Theorem 6.4, where we show that graphs with at least edges admit secret-sharing schemes with normalized total share size
. This result nearly matches the best total share size for sparse graphs with at most
edges (for which we share the secret independently for each edge). The construction follows the ideas described in the introduction.



A secret-sharing scheme realizing a graph
with
for some
.

Total share size for different families of graphs and constant . Note that almost all graphs in
and in
have
and
edges, respectively.
Let be a graph with
and
for some
. The scheme described in Fig. 3 is a secret-sharing scheme realizing G.
Let be a graph with
and
for some
. Then G can be realized by a secret-sharing schemes with secrets of size
and normalized total share size
In Theorem 6.4, we combine the secret-sharing scheme for very dense graphs in Theorem 6.1 with several instances of the first scheme of Theorem 4.5. Instead, if we replace the former by the fourth scheme of Theorem 4.5, we obtain a multi-linear secret-sharing scheme with secrets of exponential size and normalized total share size for exponentially long secrets.
In Fig. 4, we summarize the current bounds on the total share size for graphs with at most edges, graphs with at least
edges,
, and
, for constant
. Additional remarks and observations are presented in the full version of this paper [13].