MPC-as-a-Service (MPCaaS) systems enable clients to outsource privacy-preserving computations to distributed servers, offering flexibility by adapting and configuring MPC protocols to meet diverse security requirements. However, traditional MPC protocols rely on a fixed set of servers for the entire computation process, limiting scalability. Dynamic MPC (DMPC) addresses this limitation by permitting participants to join or leave during the computation. Nevertheless, existing DMPC protocols assume synchronous networks, which can lead to failures under unbounded network delays. In this paper, we present AD-MPC, the first asynchronous dynamic MPC protocol. Our protocol ensures guaranteed output delivery under optimal resilience ((n = 3t + 1)). To achieve this, we introduce two critical components: an asynchronous dynamic preprocessing protocol that facilitates the on-demand generation of Beaver triples for secure multiplication, and an asynchronous transfer protocol that maintains consistency during party hand-offs. These components collectively ensure computation correctness and transfer consistency across participants. We implement AD-MPC and evaluate its performance across up to 20 geographically distributed nodes. Experimental results demonstrate that the protocol not only offers strong security guarantees in dynamic and asynchronous network environments but also achieves performance comparable to state-of-the-art DMPC protocols.
MPC-as-a-Service (MPCaaS) systems enable clients to outsource privacy-preserving computations to distributed servers, offering flexibility by adapting and configuring MPC protocols to meet diverse security requirements. However, traditional MPC protocols rely on a fixed set of servers for the entire computation process, limiting scalability. Dynamic MPC (DMPC) addresses this limitation by permitting participants to join or leave during the computation. Nevertheless, existing DMPC protocols assume synchronous networks, which can lead to failures under unbounded network delays. In this paper, we present AD-MPC, the first asynchronous dynamic MPC protocol. Our protocol ensures guaranteed output delivery under optimal resilience ((n = 3t + 1)). To achieve this, we introduce two critical components: an asynchronous dynamic preprocessing protocol that facilitates the on-demand generation of Beaver triples for secure multiplication, and an asynchronous transfer protocol that maintains consistency during party hand-offs. These components collectively ensure computation correctness and transfer consistency across participants. We implement AD-MPC and evaluate its performance across up to 20 geographically distributed nodes. Experimental results demonstrate that the protocol not only offers strong security guarantees in dynamic and asynchronous network environments but also achieves performance comparable to state-of-the-art DMPC protocols.
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.
Abstract. Secure multiparty computation (MPC) allows a set of parties to securely evaluate any agreed function of their inputs, even when up to t of the n parties are faulty. Protocols for synchronous networks (where every sent message is assumed to arrive within a constant time) tolerate up to t < n/2 faulty parties, whereas in the more realistic asynchronous setting (with no a priory information on maximal message delay) only security against t < n/3 is possible. Note that even asynchronous Byzantine agreement requires t < n/3. In this paper, we are interested in the minimal synchronicity assumption for achieving security against t < n/2. It turns out that the bottleneck of asynchronous MPC is the distribution of the inputs: Once the inputs are correctly distributed, any deterministic function can be computed over a fully asynchronous network with t < n/2. Furthermore, we show that the inputs can be verifiably distributed with t < n/2, if a single round of synchronous broadcast is available. Composing the above, we obtain the first MPC protocol that achieves security against t < n/2 without assuming a fully synchronous network. Actually our protocol guarantees security against any faulty minority in an almost asynchronous network, i.e. in a network with one single round of synchronous broadcast (followed by a fully asynchronous communication). Furthermore our protocol takes inputs of all parties (in a fully asynchronous network only inputs of n−t parties can be guaranteed), and so achieves everything that is possible in synchronous networks (but impossible in fully asynchronous networks) at the price of just one synchronous broadcast round. As tools for our protocol we introduce the notions of almost non-interactive verifiable secret-sharing and almost non-interactive zero-knowledge proof of knowledge, which are of independent interest as they can serve as efficient replacements for fully non-interactive verifiable secret-sharing and fully non-interactive zero-knowledge proof of knowledge.
parties to securely compute an agreed function f over some finite field in the presence of a computationally unbounded adversary, who can maliciously corrupt any t out of the n parties. Most of the known efficient MPC protocols are designed in the offline- online framework introduced in a seminal work by Beaver in CRYPTO 1991. In this framework, the parties generate shared random and private multiplication-triples during the offline phase, which are used later in the online phase for securely evaluating the multiplication gates in the circuit representing f . The efficiency of the MPC protocols in this framework then relies on efficient ways of implementing the offline phase. In this paper, we propose a new and simple framework for generating shared and private random multiplication triples with unconditional security. The existing protocols approach this problem by first producing shared pairs of private and random values, followed by securely computing the shared product of each pair of values. The latter task involves a multiplication protocol for shared values that are typically communication intensive. Our framework takes a completely different approach and shuns the use of multiplication protocol. Namely, we ask the parties to verifiably share random multiplication triples and then securely extract shared random multiplication triples unknown to the adversary, from the shared triples. Realizing our framework in the asynchronous and hybrid network setting,1 we present the first ever MPC protocols with a linear (in the number of parties) communication overhead per multiplication gate in the circuit representing f . These are significant improvements over the best known existing MPC protocols in the asynchronous and hybrid network setting with communication complexity O(n2) and O(n3), respectively. Our framework when applied to the synchronous setting results in round-efficient MPC protocols.
Many services that people use daily require computation that depends on the private data of multiple parties. While the utility of the final result of such interactions outweighs the privacy concerns related to output release, the inputs for such computations are much more sensitive and need to be protected. Secure multiparty computation (MPC) considers the question of constructing computation protocols that reveal nothing more about their inputs than what is inherently leaked by the output. There have been strong theoretical results that demonstrate that every functionality can be computed securely. However, these protocols remain unused in practical solutions since they introduce efficiency overhead prohibitive for most applications. Generic multiparty computation techniques address homogeneous setups with respect to the resources available to the participants and the adversarial model. On the other hand, realistic scenarios present a wide diversity of heterogeneous environments where different participants have different available resources and different incentives to misbehave and collude. In this thesis we introduce techniques for multiparty computation that focus on heterogeneous settings. We present solutions tailored to address different types of asymmetric constraints and improve the efficiency of existing approaches in these scenarios. We tackle the question from three main directions: New Computational Models for MPC - We explore different computational models that enable us to overcome inherent inefficiencies of generic MPC solutions using circuit representation for the evaluated functionality. First, we show how we can use random access machines to construct MPC protocols that add only polylogarithmic overhead to the running time of the insecure version of the underlying functionality. This allows to achieve MPC constructions with computational complexity sublinear in the size for their inputs, which is very important for computations that use large databases. We also consider multivariate polynomials which yield more succinct representations for the functionalities they implement than circuits, and at the same time a large collection of problems are naturally and efficiently expressed as multivariate polynomials. We construct an MPC protocol for multivariate polynomials, which improves the communication complexity of corresponding circuit solutions, and provides currently the most efficient solution for multiparty set intersection in the fully malicious case. Outsourcing Computation - The goal in this setting is to utilize the resources of a single powerful service provider for the work that computationally weak clients need to perform on their data. We present a new paradigm for constructing verifiable computation (VC) schemes, which enables a computationally limited client to verify efficiently the result of a large computation. Our construction is based on attribute-based encryption and avoids expensive primitives such as fully homomorphic encryption andprobabilistically checkable proofs underlying existing VC schemes. Additionally our solution enjoys two new useful properties: public delegation and verification. We further introduce the model of server-aided computation where we utilize the computational power of an outsourcing party to assist the execution and improve the efficiency of MPC protocols. For this purpose we define a new adversarial model of non-collusion, which provides room for more efficient constructions that rely almost completely only on symmetric key operations, and at the same time captures realistic settings for adversarial behavior. In this model we propose protocols for generic secure computation that offload the work of most of the parties to the computation server. We also construct a specialized server-aided two party set intersection protocol that achieves better efficiencies for the two participants than existing solutions. Outsourcing in many cases concerns only data storage and while outsourcing the data of a single party is useful, providing a way for data sharing among different clients of the service is the more interesting and useful setup. However, this scenario brings new challenges for access control since the access control rules and data accesses become private data for the clients with respect to the service provide. We propose an approach that offers trade-offs between the privacy provided for the clients and the communication overhead incurred for each data access. Efficient Private Search in Practice - We consider the question of private search from a different perspective compared to traditional settings for MPC. We start with strict efficiency requirements motivated by speeds of available hardware and what is considered acceptable overhead from practical point of view. Then we adopt relaxed definitions of privacy, which still provide meaningful security guarantees while allowing us to meet the efficiency requirements. In this setting we design a security architecture and implement a system for data sharing based on encrypted search, which achieves only 30% overhead compared to non-secure solutions on realistic workloads.
Unconditionally secure multiparty computation (MPC) allows a set of n mutually distrusting parties to securely compute an agreed function f over some finite field in the presence of a computationally unbounded adversary, who can actively corrupt any t out of the n parties. Designing an asynchronous MPC (AMPC) protocol with a communication complexity of O(n) field elements per multiplication gate is a long standing open problem. We solve the open problem by presenting two AMPC protocols with the corruption threshold t < n/4. Our first protocol is statistically secure (i.e. involves a negligible error in the protocol outcome) in a completely asynchronous setting and improves the communication complexity of the previous best AMPC protocol in the same setting by a factor of Θ(n). Our second protocol is perfectly secure (i.e. error free) in a hybrid setting, where one round of communication is assumed to be synchronous and improves the communication complexity of the previous best AMPC protocol in the hybrid setting by a factor of Θ(n 2). Starting with the seminal work of Beaver (CRYPTO 1991), it is by now a well-known technique to evaluate multiplication gates in an MPC protocol using shared random multiplication triples. The central contribution common to both the presented protocols is a new and simple framework for generating shared random multiplication triples. All the existing protocols approach the problem by first producing shared pairs of random values, followed by computing
Secure multi-party computation (MPC) is a fundamental problem in secure distributed computing. The optimal resilience for perfectly-secure MPC in synchronous and asynchronous networks is t < n/3 and t < n/4 respectively, where n is the number of parties and t is the number of corruptions. A natural question is whether there exists a protocol tolerating ts < n/3 corruptions in a synchronous network and ta < n/4 corruptions in an asynchronous network. We design such a protocol, if 3ts + ta < n. For our protocol, we present a perfectly-secure Byzantine agreement (BA) protocol, tolerating t < n/3 corruptions in any network and a perfectly-secure verifiable secret-sharing (VSS) protocol, tolerating ts and ta corruptions in a synchronous and an asynchronous network respectively.