A key distribution scheme for dynamic conferences is a method by which initially an (off-line) trusted server distributes private individual pieces of information to a set of users. Later any group of users of a given size (a dynamic conference) is able to compute a common secure key. In this paper we study the theory and applications of such perfectly secure systems, In this setting, any group of t users can compute a common key by each user computing using only his private piece of information and the identities of the other t-1 group users. Keys are secure against coalitions of up to k users, that is, even if E users pool together their pieces they cannot compute anything about a key of any t-size conference comprised of other users. First we consider a non-interactive model where users compute the common key without any interaction. We prove a lower bound on the size of the user's piece of information of ("2; ') times the size of the common key. W e then establish the optimality of this bound, by describing and analyzing a scheme which exactly meets this limitatioii (the construction extends the one in [2]). Then, we consider the model where interaction is allowed in the common key computation phase, and show a gap between the models by exhibiting an interactive scheme in which the user's information is only k + t-1 times the size of the common key. We further show various applications and useful modifications of our basic scheme. Finally, we present its adaptation to network topologies with neighborhood constraints.

A key distribution scheme for dynamic conferences is a method by which initially an (off-line) trusted server distributes private individual pieces of information to a set of users. Later any group of users of a given size (a dynamic conference) is able to compute a common secure key. In this paper we study the theory and applications of such perfectly secure systems, In this setting, any group of t users can compute a common key by each user computing using only his private piece of information and the identities of the other t-1 group users. Keys are secure against coalitions of up to k users, that is, even if E users pool together their pieces they cannot compute anything about a key of any t-size conference comprised of other users. First we consider a non-interactive model where users compute the common key without any interaction. We prove a lower bound on the size of the user's piece of information of ("2; ') times the size of the common key. W e then establish the optimality of this bound, by describing and analyzing a scheme which exactly meets this limitatioii (the construction extends the one in [2]). Then, we consider the model where interaction is allowed in the common key computation phase, and show a gap between the models by exhibiting an interactive scheme in which the user's information is only k + t-1 times the size of the common key. We further show various applications and useful modifications of our basic scheme. Finally, we present its adaptation to network topologies with neighborhood constraints.

AbstracL A secret sharing scheme permits a secret to be shared among participants in such a way that only qualified subsets of participants can recover the secret, but any nonqualified subset has absolutely no information on the secret. The set of all qualified subsets defines the access structure to the secret. Sharing schemes are useful in the management of cryptographic keys and in multiparty secure protocols.We analyze the relationships among the entropies of the sample spaces from which the shares and the secret are chosen. We show that there are access structures with four participants for which any secret sharing scheme must give to a participant a share at least 50% greater than the secret size. This is the first proof that there exist access structures for which the best achievable information rate (i.e., the ratio between the size of the secret and that of the largest share) is bounded away from 1. The bound is the best possible, as we construct a secret sharing scheme for the above access structures that meets the bound with equality.

Group testing refers to the situation in which one is given a set of objects O, an unknown subset P ⊆ O, and the task of determining P by asking queries of the type “does P intersect Q?”, where Q is a subset of O. Group testing is a basic search paradigm that occurs in a variety of situations such as quality control testing, searching in storage systems, multiple access communications, and data compression, among others. Group testing procedures have been recently applied in computational molecular biology, where they are used for screening libraries of clones with hybridization probes and sequencing by hybridization. Motivated by particular features of group testing algorithms used in biological screening, we study the efficiency of two-stage group testing procedures. Our main result is the first optimal two- stage algorithm that uses a number of tests of the same order as the information-theoretic lower bound on the problem. We also provide efficient algorithms for the case in which there is a Bernoulli probability distribution on the possible sets P, and an optimal algorithm for the case in which the outcome of tests may be unreliable because of the presence of “inhibitory” items in O. Our results depend on a combinatorial structure introduced in this paper. We believe that it will prove useful in other contexts, too

Two mobile agents (robots) having distinct labels and located in nodes of an unknown anonymous connected graph, have to meet. We consider the asynchronous version of this well-studied rendezvous problem and we seek fast deterministic algorithms for it. Since in the asynchronous setting meeting at a node, which is normally required in rendezvous, is in general impossible, we relax the demand by allowing meeting of the agents inside an edge as well. The measure of performance of a rendezvous algorithm is its cost: for a given initial location of agents in a graph, this is the number of edge traversals of both agents until rendezvous is achieved. If agents are initially situated at a distance D in an infinite line, we show a rendezvous algorithm with cost O(D|L min | 2) when D is known and O((D + |L max |) 3) if D is unknown, where |L min | and |L max | are the lengths of the shorter and longer label of the agents, respectively. These results still hold for the case of the ring of unknown size but then we also give an optimal algorithm of cost O(n|L min |), if the size n of the ring is known, and of cost O(n|L max |), if it is unknown. For arbitrary graphs, we show that rendezvous is feasible if an upper bound on the size of the graph is known and we give an optimal algorithm of cost O(D|L min |) if the topology of the graph and the initial positions are known to agents.