We propose a mechanism for an m-party dishonest majority Multi-Party Computation (MPC) protocol to obtain the required pre-processing data (called Beaver Triples), from a subset of a set of cloud service providers; providing a form of TaaS (Triples-as-a-Service). The service providers used by the MPC computing parties can be selected dynamically at the point of the MPC computation being run, and the interaction between the MPC parties and the TaaS parties is via a single round of communication, logged on a public ledger. The TaaS is itself instantiated as an MPC protocol which produces the triples for a different access structure. Thus our protocol also acts as a translation mechanism between the secret sharing used by one MPC protocol and the other.
We propose a mechanism for an m-party dishonest majority Multi-Party Computation (MPC) protocol to obtain the required pre-processing data (called Beaver Triples), from a subset of a set of cloud service providers; providing a form of TaaS (Triples-as-a-Service). The service providers used by the MPC computing parties can be selected dynamically at the point of the MPC computation being run, and the interaction between the MPC parties and the TaaS parties is via a single round of communication, logged on a public ledger. The TaaS is itself instantiated as an MPC protocol which produces the triples for a different access structure. Thus our protocol also acts as a translation mechanism between the secret sharing used by one MPC protocol and the other.
Abstract. We present a secure honest majority MPC protocol, against a static adversary, which aims to reduce the communication cost in the situation where there are a large number of parties and the number of adversarially con-trolled parties is relatively small. Our goal is to reduce the usage of point-to-point channels among the parties, thus enabling them to run multiple different protocol executions. Our protocol has highly efficient theoretical communi-cation cost when compared with other protocols in the literature; specifically the circuit-dependent communication cost, for circuits of suitably large depth, is O(|ckt|κ7), for security parameter κ and circuit size |ckt|. Our protocol finds application in cloud computing scenario, where the fraction of corrupted parties is relatively small. By mini-mizing the usage of point-to-point channels, our protocol can enable a cloud service provider to run multiple MPC protocols. 1
Secure multi-party computation (MPC) allows a set of parties to compute a function jointly while keeping their inputs private. Compared with the MPC based on garbled circuits, some recent research results show that MPC based on secret sharing (SS) works at a very high speed. Moreover, SS-based MPC can be easily vectorized and achieve higher throughput. In SS-based MPC, however, we need many communication rounds for computing concrete protocols like equality check, less-than comparison, etc. This property is not suited for large-latency environments like the Internet (or WAN). In this paper, we construct semi-honest secure communication-efficient two-party protocols. The core technique is Beaver triple extension, which is a new tool for treating multi-fan-in gates, and we also show how to use it efficiently. We mainly focus on reducing the number of communication rounds, and our protocols also succeed in reducing the number of communication bits (in most cases). As an example, we propose a less-than comparison protocol (under practical parameters) with three communication rounds. This is less than a half compared with the previous work. Moreover, the number of communication bits is also 38.4% fewer. As a result, total online execution time is 56.1% shorter than the previous work adopting the same settings. Although the computation costs of our protocols are more expensive than those of previous work, we confirm via experiments that such a disadvantage has small effects on the whole online performance in the typical WAN environments.
We initiate the study of secure multi-party computation (MPC) in a server-aided setting, where the parties have access to a single server that (1) does not have any input to the computation; (2) does not receive any output from the computation; but (3) has a vast (but bounded) amount of computational resources. In this setting, we are concerned with designing protocols that minimize the computation of the parties at the expense of the server. We develop new definitions of security for this server-aided setting that generalize the standard simulation-based definitions for MPC and allow us to formally capture the existence of dishonest but non-colluding participants. This requires us to introduce a formal characterization of non-colluding adversaries that may be of independent interest. We then design general and special-purpose server-aided MPC protocols that are more efficient (in terms of computation and communication) for the parties than the alternative of running a standard MPC protocol (i.e., without the server). Our main general-purpose protocol provides security when there is at least one honest party with input. We also construct a new and efficient server-aided protocol for private set intersection and give a general transformation from any secure delegated computation scheme to a server-aided two-party protocol. ∗Microsoft Research. senyk@microsoft.com. †University of Calgary. pmohassel@cspc.ucalgary.ca. Work done while visiting Microsoft Research. ‡Columbia University. mariana@cs.columbia.edu. Work done as an intern at Microsoft Research.
We put forth a new paradigm for secure multi-party computation (MPC) in the preprocessing model, where a feasible one-time setup can enable a lifetime of efficient online secure computations. Our protocols match the security guarantees and low costs of the cheapest category of MPC solutions, namely 3-party protocols (3PC) secure against a single malicious party, with the qualitative advantages that one party communicates data sublinear in the circuit size, and can go offline after its initial messages. This “2+ 1“-party structure can alternatively be instantiated between 2 parties with the aid of an (untrusted) dealer. Within such existing protocols, we provide comparable online performance while improving the storage and offline dealer-to-party communication requirements by more than 3 orders of magnitude. At the technical level, we build on the Fully Linear Interactive Oracle Proof (FLIOP)-based protocol design of Boyle et al. (CRYPTO 2021). We provide an extensive assortment of algorithmic and implementation-level optimizations, design efficient distributed proofs of well-formedness of complex FLIOP correlations, and make them circuit-independent. We implement and benchmark our end-to-end system against the state of the art in the 2+1 regime, a dealer-aided variant of SPDZ for Boolean circuits. We additionally extend our techniques to the(n+1)party setting, where a dealer aids general dishonest-majority MPC, and provide a variant of the protocol which further achieves security with “identifiable abort.”
Abstract. As an extension of multi-party computation (MPC), we propose the concept of secure parallel multi-party computation which is to securely compute multi-functions against an adversary with multistructures. Precisely, there are m functions f1,..., fm and m adversary structures A1,..., Am, where fi is required to be securely computed against an Ai-adversary. We give a general construction to build a parallel multi-party computation protocol from any linear multi-secret sharing scheme (LMSSS), provided that the access structures of the LMSSS allow MPC at all. When computing complicated functions, our protocol has more advantage in communication complexity than the “direct sum” method which actually executes a MPC protocol for each function. The paper also provides an efficient and generic construction to obtain from any LMSSS a multiplicative LMSSS for the same multi-access structure. 1
Secure multiparty computation (MPC) enables privacy-preserving collaborative computation over sensitive data held by multiple mutually distrusting parties. Unfortunately, in the most natural setting where a majority of the parties are maliciously corrupt (also called the dishonest majority setting), traditional MPC protocols incur high overheads and offer weaker security guarantees than are desirable for practical applications. In this paper, we explore the possibility of circumventing these drawbacks and achieving practically efficient dishonest majority MPC protocols with strong security guarantees by assuming an additional semi-honest, non-colluding helper party HP .1We believe that this is a more realistic alternative to assuming an honest majority, since many real-world applications of MPC involving potentially large numbers of parties (such as dark pools) are typically enabled by a central governing entity that can be modeled as the HP.In the above model, we are the first to design, implement and benchmark a practically-efficient and general multi-party framework, Asterisk. Our framework requires invoking HP only a constant number of times, achieves the strong security guarantee of fairness (either all parties learn the output or none do), scales to hundreds of parties, outperforms all existing dishonest majority MPC protocols, and is, in fact, competitive with state-of-the-art honest majority MPC protocols. Our experiments show that Asterisk achieves 228 – 288× speedup in preprocessing as compared to the best dishonest majority MPC protocol. With respect to online time, Asterisk supports 100-party evaluation of a circuit with 106multiplication gates in approximately 20 seconds. We also implement and benchmark practically efficient and highly scalable dark pool instances using Asterisk. The corresponding run times showcase the effectiveness of Asterisk in enabling efficient realizations of real-world privacy-preserving applications with strong security guarantees.