We describe scalable algorithms for secure multiparty computation (SMPC). We assume a synchronous message passing communication model, but unlike most related work, we do not assume the existence of a broadcast channel. Our main result holds for the case where there are n players, of which a 1/3 − fraction are controlled by an adversary, for any positive constant. We describe a SMPC algorithm for this model that requires each player to send Õ(n+mn + n) messages and perform Õ(n+mn + n) computations to compute any function f, where m is the size of a circuit to compute f. We also consider a model where all players are selfish but rational. In this model, we describe a Nash equilibrium protocol that solve SMPC and requires each player to send Õ(n+mn) messages and perform Õ( n+m n) computations. These results significantly improve over past results for SMPC which require each player to send a number of bits and perform a number of computations that is θ(nm). ar X iv
We describe scalable algorithms for secure multiparty computation (SMPC). We assume a synchronous message passing communication model, but unlike most related work, we do not assume the existence of a broadcast channel. Our main result holds for the case where there are n players, of which a 1/3 − fraction are controlled by an adversary, for any positive constant. We describe a SMPC algorithm for this model that requires each player to send Õ(n+mn + n) messages and perform Õ(n+mn + n) computations to compute any function f, where m is the size of a circuit to compute f. We also consider a model where all players are selfish but rational. In this model, we describe a Nash equilibrium protocol that solve SMPC and requires each player to send Õ(n+mn) messages and perform Õ( n+m n) computations. These results significantly improve over past results for SMPC which require each player to send a number of bits and perform a number of computations that is θ(nm). ar X iv
We describe scalable algorithms for secure multiparty computation (SMPC). We assume a synchronous message passing communication model, but we do not assume the existence of a broadcast channel. Our main result holds for the case where there are n players, of which a 1/3-ε fraction are controlled by an adversary, for ε any positive constant. We describe an SMPC algorithm for this model that requires each player to send Õ(⁄n+mn + √n) messages and perform Õ(⁄n+mn + √n) computations to compute any function f, where m is the size of a circuit to compute f. We also consider a model where all players are rational. In this model, we describe a Nash equilibrium protocol that solves SMPC and requires each player to send Õ(⁄n+mn) messages and perform Õ(⁄n+mn) computations. These results significantly improve over past results for SMPC which require each player to send a number of bits and perform a number of computations that is Θ(n, m)
Multiparty computation (MPC) is a powerful and generic cryptographic framework capable of realizing essentially any cryptographic task (functionality) while preserving privacy and robustness. In the MPC model, a group of mutually distrustful parties seek to jointly compute a function f of their privately held inputs x1, ..., xn, while revealing no information about those inputs beyond what is entailed by the function output(s). Some portion of these players may be corrupted, controlled by a centralized adversary who directs their (mis)behavior and seeks to gain information on private inputs or to disrupt the protocol execution.
In this work, we examine the resource requirements of information-theoretically secure multiparty computation. In particular, we look at trade-offs involving what we call assumptions, by which we mean two aspects of the model's setup: (1) the extent to which parties are connected by secure, pairwise communication channels; and (2) the usage (as a black box) of a channel—a primitive which enforces consistency among views by allowing a single party to send a message to all other parties which is guaranteed to be consistent, even if the broadcaster is corrupted.
Part I of this work focuses on the first network-model assumption, that of the graph's connectivity by pairwise channels. We show upper and lower bounds on communication complexity in the Secure Message Transmission with Public Discussion (SMT-PD) model, as a function of the threshold of corrupted parties. The SMT-PD model, which abstracts the problem of secure communication over a partially connected network, includes two components: a public and a set of simple channels. We show significant improvements in both areas: on the channel, we reduce communication to logarithmic in terms of the message's bit-length m, where the previous best result was linear in m; on the simple channels, we reduce from O(mn) to O(mn/(n−t)), where n is the number of simple channels and t is a bound on the number of corrupted channels. Using tools from information theory, we show this amount of simple-wire communication is essentially optimal. Finally, we give an amortized solution which drastically improves communication over channel when the protocol is repeated many times sequentially.
Part II shifts focus to the second network-model assumption, the use of an atomic broadcast primitive. Here we show that three broadcast rounds suffice for general secure computation, while two broadcast rounds are necessary. In particular we show that even for the natural and important functionality of Weak Secret Sharing—a type of distributed commitment—there is no protocol which uses only a single broadcast and achieves better than an explicit constant probability of success (so the protocol's success cannot be a function of a security parameter).
Secure multiparty computation (MPC) is perhaps the most popular paradigm in the area of cryptographic protocols. It allows several mutually untrustworthy parties to jointly compute a function of their private inputs, without revealing to each other information about those inputs. In the case of unconditional (information-theoretic) security, protocols are known which tolerate a dishonest minority of players, who may coordinate their attack and deviate arbitrarily from the protocol specification. It is typically assumed in these results that parties are connected pairwise by authenticated, private channels, and that in addition they have access to a “broadcast ” channel. Broadcast allows one party to send a consistent message to all other parties, guaranteeing consistency even if the broadcaster is corrupted. Because broadcast cannot be simulated on the point-to-point network when more than a third of the parties are corrupt, it is impossible to construct general MPC protocols in this setting without using a broadcast channel (or some equivalent addition to the model). A great deal of research has focused on increasing the efficiency of MPC, primarily in terms of round complexity and communication complexity. In this work we propose a refinement of the round complexity which we term broadcast complexity. We view the broadcast channel as an expensive resource
We describe scalable protocols for solving the secure multi-party computation (MPC) problem among a large number of parties. We consider both the synchronous and the asynchronous communication models. In the synchronous setting, our protocol is secure against a static malicious adversary corrupting less than a 1/3 fraction of the parties. In the asynchronous setting, we allow the adversary to corrupt less than a 1/8 fraction of parties. For any deterministic function that can be computed by an arithmetic circuit with m gates, both of our protocols require each party to send a number of field elements and perform an amount of computation that is O~(m/n+n). We also show that our protocols provide perfect and universally-composable security. To achieve our asynchronous MPC result, we define the \emph{threshold counting problem} and present a distributed protocol to solve it in the asynchronous setting. This protocol is load balanced, with computation, communication and latency complexity of O(logn), and can also be used for designing other load-balanced applications in the asynchronous communication model.
Abstract. A multiparty computation (MPC) protocol allows a set of players to compute a function of their inputs while keeping the inputs private and at the same time securing the correctness of the output. Most MPC protocols assume that the adversary can corrupt up to a fixed fraction of the number of players. Hirt and Maurer initiated the study of MPC under more general corruption patterns, in which the adversary is allowed to corrupt any set of players in some pre-defined collection of sets [6]. In this paper we consider this important direction of research and present significantly improved communication complexity of MPC protocols for general adversary structures. More specifically, ours is the first unconditionally secure protocol that achieves linear communication in the size of Monotone Span Program representing the adversary structure in the malicious setting against any Q2 adversary structure, whereas all previous protocols were at least cubic.
Abstract. In this note, we report on the first large-scale and practical application of multiparty computation, which took place in January 2008. We also report on the novel cryptographic protocols that were used. 1 Introduction and History In multiparty computation (MPC), we consider a number of players P1,..., Pn, who initially each hold inputs x1,..., xn, and we then want to securely compute some function f on these inputs, where f(x1,..., xn) = (y1,..., yn), such that Pi learns yi but no other information. This should hold, even if players exhibit some amount of adversarial behavior. The goal can be accomplished by an interactive