We prove two classes of lower bounds on the communication complexity of information-theoretically secure multiparty computation. The first lower bound applies to perfect passive secure multiparty computation in the standard model with n = 2t+1 parties of which t are corrupted. We show a lower bound that applies to secure evaluation of any function, assuming that each party can choose to learn or not learn the output. Specifically, we show that there is a function H^* such that for any protocol that evaluates y_i = b_i ⋅ f(x₁,...,x_n) with perfect passive security (where b_i is a private boolean input), the total communication must be at least 1/2 ∑_{i = 1}ⁿ H_f^*(x_i) bits of information. The second lower bound applies to the perfect maliciously secure setting with n = 3t+1 parties. We show that for any n and all large enough S, there exists a reactive functionality F_S taking an S-bit string as input (and with short output) such that any protocol implementing F_S with perfect malicious security must communicate Ω(nS) bits. Since the functionalities we study can be implemented with linear size circuits, the result can equivalently be stated as follows: for any n and all large enough g ∈ ℕ there exists a reactive functionality F_C doing computation specified by a Boolean circuit C with g gates, where any perfectly secure protocol implementing F_C must communicate Ω(n g) bits. The results easily extends to constructing similar functionalities defined over any fixed finite field. Using known techniques, we also show an upper bound that matches the lower bound up to a constant factor (existing upper bounds are a factor lg n off for Boolean circuits). Both results also extend to the case where the threshold t is suboptimal. Namely if n = kt+s the bound is weakened by a factor O(s), which corresponds to known optimizations via packed secret-sharing.
We prove two classes of lower bounds on the communication complexity of information-theoretically secure multiparty computation. The first lower bound applies to perfect passive secure multiparty computation in the standard model with n = 2t+1 parties of which t are corrupted. We show a lower bound that applies to secure evaluation of any function, assuming that each party can choose to learn or not learn the output. Specifically, we show that there is a function H^* such that for any protocol that evaluates y_i = b_i ⋅ f(x₁,...,x_n) with perfect passive security (where b_i is a private boolean input), the total communication must be at least 1/2 ∑_{i = 1}ⁿ H_f^*(x_i) bits of information. The second lower bound applies to the perfect maliciously secure setting with n = 3t+1 parties. We show that for any n and all large enough S, there exists a reactive functionality F_S taking an S-bit string as input (and with short output) such that any protocol implementing F_S with perfect malicious security must communicate Ω(nS) bits. Since the functionalities we study can be implemented with linear size circuits, the result can equivalently be stated as follows: for any n and all large enough g ∈ ℕ there exists a reactive functionality F_C doing computation specified by a Boolean circuit C with g gates, where any perfectly secure protocol implementing F_C must communicate Ω(n g) bits. The results easily extends to constructing similar functionalities defined over any fixed finite field. Using known techniques, we also show an upper bound that matches the lower bound up to a constant factor (existing upper bounds are a factor lg n off for Boolean circuits). Both results also extend to the case where the threshold t is suboptimal. Namely if n = kt+s the bound is weakened by a factor O(s), which corresponds to known optimizations via packed secret-sharing.
Secure multiparty computation (MPC) is a cryptographic primitive which enables multiple parties to jointly compute a function without revealing any extra information on their private inputs. Bottleneck complexity is an efficiency measure that captures the load-balancing aspect of MPC protocols, defined as the maximum amount of communication required by any party. In this work, we study the problem of establishing lower bounds on the bottleneck complexity of MPC protocols. While the previously known techniques for lower bounding total communication complexity can also be applied to bottleneck complexity, they do not provide nontrivial bounds in the correlated randomness model, which is commonly assumed by existing protocols achieving low bottleneck complexity, or they are applied only to functions of limited practical interest. We propose several novel techniques for lower bounding the bottleneck complexity of MPC protocols. Our methods derive nontrivial lower bounds even in the correlated randomness model and apply to practically relevant functions including the sum function and threshold functions. Furthermore, our lower bounds demonstrate the optimality of some existing MPC protocols in terms of bottleneck complexity or the amount of correlated randomness.
Abstract We construct the first actively-secure Multi-Party Computation (MPC) protocols with an arbitrary number of parties in the dishonest majority setting, for an arbitrary field F F with constant communication overhead over the “passive-GMW” protocol (Goldreich, Micali and Wigderson, STOC ‘87). Our protocols rely on passive implementations of Oblivious Transfer (OT) in the Boolean setting and Oblivious Linear function Evaluation (OLE) in the arithmetic setting. Previously, such protocols were only known over sufficiently large fields (Genkin et al. STOC ‘14) or a constant number of parties (Ishai et al. CRYPTO ‘08). Conceptually, our protocols are obtained via a new compiler from a passively-secure protocol for a distributed multiplication functionality FMULT F MULT , to an actively-secure protocol for general functionalities. Roughly, FMULT F MULT is parameterized by a linear-secret sharing scheme S S , where it takes S S -shares of two secrets and returns S S -shares of their product. We show that our compilation is concretely efficient for sufficiently large fields, resulting in an overhead of 2 when securely computing natural circuits. Our compiler has two additional benefits: (1) It can rely on any passive implementation of FMULT F MULT , which, besides the standard implementation based on OT (for Boolean) and OLE (for arithmetic), allows us to rely on implementations based on threshold cryptosystems (Cramer et al. Eurocrypt ‘01), and (2) it can rely on weaker-than-passive (i.e., imperfect/leaky) implementations, which in some parameter regimes yield actively-secure protocols with overhead less than 2. Instantiating this compiler with an “honest-majority” implementation of FMULT F MULT , we obtain the first honest-majority protocol (with up to one-third corruptions) for Boolean circuits with constant communication overhead over the best passive protocol (Damgård and Nielsen, CRYPTO ‘07).
Over the past 20 years, the efficiency of secure multi-party protocols has been greatly improved. While the seminal protocols from the late 80’s require a communication of Ω(n⁶) field elements per multiplication among n parties, recent protocols offer linear communication complexity. This means that each party needs to communicate a constant number of field elements per multiplication, independent of n. However, these efficient protocols only offer active security, which implies that at most t<n/3 (perfect security), respectively t<n/2 (statistical or computational security) parties may be corrupted. Higher corruption thresholds (i.e., t≥ n/2) can only be achieved with degraded security (unfair abort), where one single corrupted party can prevent honest parties from learning their outputs. The aforementioned upper bounds (t<n/3 and t<n/2) have been circumvented by considering mixed adversaries (Fitzi et al., Crypto' 98), i.e., adversaries that corrupt, at the same time, some parties actively, some parties passively, and some parties in the fail-stop manner. It is possible, for example, to achieve perfect security even if 2/3 of the parties are faulty (three quarters of which may abort in the middle of the protocol, and a quarter may even arbitrarily misbehave). This setting is much better suited to many applications, where the crash of a party is more likely than a coordinated active attack. Surprisingly, since the presentation of the feasibility result for the mixed setting, no progress has been made in terms of efficiency: the state-of-the-art protocol still requires a communication of Ω(n⁶) field elements per multiplication. In this paper, we present a perfectly-secure MPC protocol for the mixed setting with essentially the same efficiency as the best MPC protocols for the active-only setting. For the first time, this allows to tolerate faulty majorities, while still providing optimal efficiency. As a special case, this also results in the first fully-secure MPC protocol secure against any number of crashing parties, with optimal (i.e., linear in n) communication. We provide simulation-based proofs of our construction.
In STOC 1988, Ben-Or, Goldwasser, and Wigderson (BGW) established an important milestone in the fields of cryptography and distributed computing by showing that every functionality can be computed with perfect (information-theoretic and error-free) security at the presence of an active (aka Byzantine) rushing adversary that controls up to n/3 of the parties. We study the round complexity of general secure multiparty computation in the BGW model. Our main result shows that every functionality can be realized in only four rounds of interaction, and that some functionalities cannot be computed in three rounds. This completely settles the round-complexity of perfect actively-secure optimally-resilient MPC, resolving a long line of research. Our lower-bound is based on a novel round-reduction technique that allows us to lift existing three-round lower-bounds for verifiable secret sharing to four-round lower-bounds for general MPC. To prove the upper-bound, we develop new round-efficient protocols for computing degree-2 functionalities over large fields, and establish the completeness of such functionalities. The latter result extends the recent completeness theorem of Applebaum, Brakerski and Tsabary (TCC 2018, Eurocrypt 2019) that was limited to the binary field.
Secure Multiparty Computation (MPC) is an expression encompassing cryptographic techniques that allow mutually distrustful parties to jointly perform computations over private data, ensuring correctness and preserving privacy despite malicious behavior. Guaranteed output is the strongest security goal for MPC: protocols with this property always deliver results. This is in contrast with weaker notions that allow malicious aborts. The seminal works of Ben-Or, Goldwasser, and Wigderson (STOC’88) and Rabin and Ben-Or (STOC’89) showed interactive protocols to compute any function with guaranteed output and perfect security if fewer than one third of parties are corrupted, or with statistical security (with a small error probability) if fewer than half are corrupted. These results hold when the set of participants is fixed throughout the execution. Ostrovsky and Yung’s proactive model (PODC’91) relaxes this assumption by allowing the set of corrupted parties to evolve over time, better capturing the dynamics of long-lived computations, where machines may be periodically compromised and recovered. The recent YOSO (You Only Speak Once) and fluid MPC models (CRYPTO’21) push this ambitious modelling even further by allowing for fully dynamic participation, with parties joining and leaving the computation at will. In this setting, known protocols with guaranteed output fall short of optimal resilience or rely on non-standard communication and adversarial assumptions. Matching the classical BGW and Rabin–Ben-Or bounds in these settings remained an open problem. We resolve these questions within the Layered MPC abstraction of David et al. (CRYPTO’23), in which the interaction pattern of a protocol is restricted to be a layered graph, meaning parties are partitioned into a sequence of disjoint sets (layers) and can send private and broadcast messages to parties in immediately subsequent layers. We match the BGW and Rabin and Ben-Or bounds in this model, fully characterizing the feasibility landscape of Layered MPC with guaranteed output. As a stepping stone towards our statistically secure protocol, we construct a more efficient and conceptually simpler computationally secure protocol relying on linear non-interactive commitments. Our results yield optimally-resilient and maximally-proactive MPC protocols with guaranteed output for both perfect and statistical security.
Non-interactive secure multiparty computation is a method to share and compute a private functionfamongnparties holding private inputs xi with 1nin the information theoretical setting. Each party locally computes a message from a share offand send it to a referee in parallel. The referee obtains the output f (xi,… , xn) while keepingfand xi private other than what can be inferred from the output. The communication complexity is evaluated by the maximum length of shares and messages. In the previous work, several kinds of function families, upper and lower bounds have been improved and the only gaps remaining are for the group products and the Abelian programs (including symmetric functions). This paper improves the communication complexity of both function families towards the optimum by deriving a new lower bound for the group products that matches the previous upper bound (up to a constant factor) and the first asymptotically optimal upper bound for the Abelian programs.