International Association for Cryptologic Research

International Association
for Cryptologic Research


Ariel Nof


Secure Multiparty Computation with Sublinear Preprocessing 📺
A common technique for enhancing the efficiency of secure multiparty computation (MPC) with dishonest majority is via {\em preprocessing}: In an offline phase, parties engage in an input-independent protocol to securely generate correlated randomness. Once inputs are known, the correlated randomness is consumed by a ``non-cryptographic'' and highly efficient online protocol. The correlated randomness in such protocols traditionally comes in two flavors: multiplication triples (Beaver, Crypto '91), which suffice for security against semi-honest parties, and {\em authenticated} multiplication triples (Bendlin et al., Eurocrypt '11, Damg{\aa}rd et al., Crypto '12) that yield efficient protocols against malicious parties. Recent constructions of pseudorandom correlation generators (Boyle et al., Crypto '19, '20) enable concretely efficient secure generation of multiplication triples with {\em sublinear communication complexity}. However, these techniques do not efficiently apply to authenticated triples, except in the case of secure two-party computation of arithmetic circuits over large fields. In this work, we propose the first {\em concretely efficient} approach for (malicious) MPC with preprocessing in which the offline communication is {\em sublinear} in the circuit size. More specifically, the offline communication scales with the {\em square root} of the circuit size. From a feasibility point of view, our protocols can make use of any secure protocol for generating (unauthenticated) multiplication triples together with any {\em additive} homomorphic encryption. We propose concretely efficient instantiations (based on strong but plausible ``linear-only'' assumptions) from existing homomorphic encryption schemes and pseudorandom correlation generators. Our technique is based on a variant of a recent protocol of Boyle et al. (Crypto '21) for MPC with preprocessing. As a result, our protocols inherit the succinct correlated randomness feature of the latter protocol.
Sublinear GMW-Style Compiler for MPC with Preprocessing 📺
We consider the efficiency of protocols for secure multiparty computation (MPC) with a dishonest majority. A popular approach for the design of such protocols is to employ {\em preprocessing}. Before the inputs are known, the parties generate correlated secret randomness, which is consumed by a fast and ``information-theoretic'' online protocol. A powerful technique for securing such protocols against malicious parties uses {\em homomorphic MACs} to authenticate the values produced by the online protocol. Compared to a baseline protocol, which is only secure against semi-honest parties, this involves a significant increase in the size of the correlated randomness, by a factor of up to a statistical security parameter. Different approaches for partially mitigating this extra storage cost come at the expense of increasing the online communication. In this work we propose a new technique for protecting MPC with preprocessing against malicious parties. We show that for circuit evaluation protocols that satisfy mild security and structural requirements, that are met by almost all standard protocols with semi-honest security, the extra {\em additive} storage and online communication costs are both {\em logarithmic} in the circuit size. This applies to Boolean circuits and to arithmetic circuits over fields or rings, and to both information-theoretic and computationally secure protocols. Our protocol can be viewed as a sublinear information-theoretic variant of the celebrated ``GMW compiler'' that applies to MPC with preprocessing. Our compiler makes a novel use of the techniques of Boneh et al. (Crypto 2019) for sublinear distributed zero knowledge, which were previously only used in the setting of {\em honest-majority} MPC.
Generalized Pseudorandom Secret Sharing and Efficient Straggler-Resilient Secure Computation 📺
Secure multiparty computation (MPC) enables $n$ parties, of which up to $t$ may be corrupted, to perform joint computations on their private inputs while revealing only the outputs. Optimizing the asymptotic and concrete costs of MPC protocols has become an important line of research. Much of this research focuses on the setting of an honest majority, where $n \ge 2t+1$, which gives rise to concretely efficient protocols that are either information-theoretic or make a black-box use of symmetric cryptography. Efficiency can be further improved in the case of a {\em strong} honest majority, where $n>2t+1$. Motivated by the goal of minimizing the communication and latency costs of MPC with a strong honest majority, we make two related contributions. \begin{itemize}[leftmargin=*] \item {\bf Generalized pseudorandom secret sharing (PRSS).} Linear correlations serve as an important resource for MPC protocols and beyond. PRSS enables secure generation of many pseudorandom instances of such correlations without interaction, given replicated seeds of a pseudorandom function. We extend the PRSS technique of Cramer et al.\ (TCC 2015) for sharing degree-$d$ polynomials to new constructions leveraging a particular class of combinatorial designs. Our constructions yield a dramatic efficiency improvement when the degree $d$ is higher than the security threshold $t$, not only for standard degree-$d$ correlations but also for several useful generalizations. In particular, correlations for locally converting between slot configurations in ``share packing'' enable us to avoid the concrete overhead of prior works. \item {\bf Cheap straggler resilience.} In reality, communication is not fully synchronous: protocol executions suffer from variance in communication delays and occasional node or message-delivery failures. We explore the benefits of PRSS-based MPC with a strong honest majority toward robustness against such failures, in turn yielding improved latency delays. In doing so we develop a novel technique for defending against a subtle ``double-dipping'' attack, which applies to the best existing protocols, with almost no extra cost in communication or rounds. \end{itemize} Combining the above tools requires further work, including new methods for batch verification via distributed zero-knowledge proofs (Boneh et al., CRYPTO 2019) that apply to packed secret sharing. Overall, our work demonstrates new advantages of the strong honest majority setting, and introduces new tools---in particular, generalized PRSS---that we believe will be of independent use within other cryptographic applications.
Concretely-Efficient Zero-Knowledge Arguments for Arithmetic Circuits and Their Application to Lattice-Based Cryptography 📺
Carsten Baum Ariel Nof
In this work we present a new interactive Zero-Knowledge Argument of knowledge for general arithmetic circuits. Our protocol is based on the “MPC-in-the-head”-paradigm of Ishai et al. (STOC 2009) and follows the recent “MPC-in-the-head with Preprocessing” as proposed by Katz, Kolesnikov and Wang (ACM CCS 2018). However, in contrast to Katz et al. who used the “cut-and-choose” approach for pre-processing, we show how to incorporate the well-known “sacrificing” paradigm into “MPC-in-the-head”, which reduces the proof size when working over arithmetic circuits. Our argument system uses only lightweight symmetric-key primitives and utilizes a simplified version of the so-called SPDZ-protocol. Based on specific properties of our protocol we then show how it can be used to construct an efficient Zero-Knowledge Argument of Knowledge for instances of the Short Integer Solution (SIS) problem. We present different protocols that are tailored to specific uses of SIS, while utilizing the advantages of our scheme. In particular, we present a variant of our argument system that allows the parties to sample the circuit “on the fly”, which may be of independent interest. We furthermore implemented our Zero-Knowledge argument for SIS and show that using our protocols it is possible to run a complete interactive proof, even for general SIS instances which result in a circuit with $${>}10^6$$ gates, in less than 0.5 s .
Efficient Fully Secure Computation via Distributed Zero-Knowledge Proofs 📺
Secure computation protocols enable mutually distrusting parties to compute a function of their private inputs while revealing nothing but the output. Protocols with {\em full security} (also known as {\em guaranteed output delivery}) in particular protect against denial-of-service attacks, guaranteeing that honest parties receive a correct output. This feature can be realized in the presence of an honest majority, and significant research effort has gone toward attaining full security with good asymptotic and concrete efficiency. We present a fully secure protocol for {\em any constant} number of parties $n$ and $t<n/2$ corruptions that achieves full security with the {\em same amortized communication} as for semi-honest security: $\frac{3t}{2t+1}|C| + o(|C|)$ $R$-elements per party ($\approx 1.5$ $R$-elements), for a circuit with $|C|$ multiplication gates over either a finite field $R=\FF$ or over the ring $R=\Z_{2^k}$. Our techniques include new methods for utilizing the distributed zero-knowledge proofs of Boneh {\em et al.} (CRYPTO 2019) for both distributed verifiers {\em and} provers. As a secondary contribution, we show that similar techniques can be used to compile the best known honest-majority protocols for an arbitrary (super-constant) number of semi-honest parties into ones that achieve {\em security with abort} against malicious parties, with sublinear additive cost. We present an efficient protocol for {\em any constant} number of parties $n$, with full security against $t<n/2$ corrupted parties, that makes a black-box use of a pseudorandom generator. Our protocol evaluates an arithmetic circuit $C$ over a finite ring $R$ (either a finite field or $R=\Z_{2^k}$) with communication complexity of $\frac{3t}{2t+1}S + o(S)$ $R$-elements per party, where $S$ is the number of multiplication gates in $C$ (namely, $<1.5$ elements per party per gate). This matches the best known protocols for the semi-honest model up to the sublinear additive term. For a small number of parties $n$, this improves over a recent protocol of Goyal {\em et al.} (Crypto 2020) by a constant factor for circuits over large fields, and by at least an $\Omega(\log n)$ factor for Boolean circuits or circuits over rings. Our protocol provides new methods for applying the distributed zero-knowledge proofs of Boneh {\em et al.}~(Crypto 2019), which only require logarithmic communication, for compiling semi-honest protocols into fully secure ones in the more challenging case of $t>1$ corrupted parties. %Similarly to the recent fully secure 3-party protocol of Boyle {\em et al.} (CCS 2019), our protocol builds on the sublinear-communication distributed zero-knowledge proofs of Boneh {\em et al.} (Crypto 2019) to compile any ``natural'' semi-honest protocol into a fully secure protocol. However, applying this tool with $t>1$ corrupted parties introduces several nontrivial challenges that we overcome in this work. Our protocol relies on {\em replicated secret sharing} to minimize communication and simplify the mechanism for achieving full security. This results in computational cost that scales exponentially with $n$. Our main protocol builds on a new honest-majority protocol for verifying the correctness of multiplication triples by making a {\em general} use of distributed zero-knowledge proofs. While the protocol only achieves the weaker notion of {\em security with abort}, it applies to any linear secret-sharing scheme and provides a conceptually simpler, more general, and more efficient alternative to previous protocols from the literature. In particular, it can be combined with the Fiat-Shamir heuristic to simultaneously achieve logarithmic communication complexity and constant round complexity.
Fast Large-Scale Honest-Majority MPC for Malicious Adversaries 📺
Protocols for secure multiparty computation enable a set of parties to compute a function of their inputs without revealing anything but the output. The security properties of the protocol must be preserved in the presence of adversarial behavior. The two classic adversary models considered are semi-honest (where the adversary follows the protocol specification but tries to learn more than allowed by examining the protocol transcript) and malicious (where the adversary may follow any arbitrary attack strategy). Protocols for semi-honest adversaries are often far more efficient, but in many cases the security guarantees are not strong enough.In this paper, we present new protocols for securely computing any functionality represented by an arithmetic circuit. We utilize a new method for verifying that the adversary does not cheat, that yields a cost of just twice that of semi-honest protocols in some settings. Our protocols are information-theoretically secure in the presence of a malicious adversaries, assuming an honest majority. We present protocol variants for small and large fields, and show how to efficiently instantiate them based on replicated secret sharing and Shamir sharing. As with previous works in this area aiming to achieve high efficiency, our protocol is secure with abort and does not achieve fairness, meaning that the adversary may receive output while the honest parties do not.We implemented our protocol and ran experiments for different numbers of parties, different network configurations and different circuit depths. Our protocol significantly outperforms the previous best for this setting (Lindell and Nof, CCS 2017); for a large number of parties, our implementation runs almost an order of magnitude faster than theirs.