A threshold signature is an advanced protocol that splits a secret signing key among multiple parties, allowing any subset above a threshold to jointly generate a signature. While post-quantum (PQ) threshold signatures are actively being studied --- especially in response to NIST's recent call for threshold schemes --- most existing solutions are tailored to specially designed, threshold-friendly signature schemes. In contrast, many real-world applications, such as distributed certificate...

One of the main shortcomings of classical distributed cryptography is its reliance on a certain fraction of participants remaining honest. Typically, honest parties are assumed to follow the protocol and not leak any information, even if behaving dishonestly would benefit them economically. More realistic models used in blockchain consensus rely on weaker assumptions, namely that no large coalition of corrupt parties exists, although every party can act selfishly. This is feasible since, in...

Secure Multi-Party Computation (MPC) is becoming more and more usable in practice. The practicality origins primarily from well-established general-purpose MPC frameworks, such as MP-SPDZ. However, to evaluate the practicality of an MPC program in the envisioned environments, still many benchmarks need to be done. We identified three challenges in the context of performance evaluations within the MPC domain: first, the cumbersome process to holistically benchmark MPC programs; second, the...

The VOLE-in-the-Head (VOLEitH) paradigm transforms VOLE-based zero-knowledge proofs into post-quantum signature schemes by allowing public verification. We introduce reduced VOLE-in-the-Head (rVOLEitH), which incorporates the Vector Semi-Commitment (VSC) technique. VSC, originally developed for MPC-in-the-Head (MPCitH) schemes, reduces commitment size while maintaining security by relaxing the binding property. We adapt the ideal cipher version of VSC (IC-VSC) into the VOLEitH framework,...

Three-party secret sharing-based computation has emerged as a promising approach for secure deep learning, benefiting from its high throughput. However, it still faces persistent challenges in computing complex operations such as secure Sign-Bit Extraction, particularly in high-latency and low-bandwidth networks. A recent work, Aegis (Lu et al., Cryptology ePrint'2023), made significant strides by proposing a constant-round DGK-style Sign-Bit Extraction protocol with GPU acceleration on...

Oblivious RAMs (ORAMs) allow data outsourcing to servers so that the access pattern to the outsourced data is kept private. It is also a crucial building block to enable private RAM access within secure multi-party computation (MPC). In recent years, schemes that match the ORAM lower bound have been proposed in both the outsourcing setting and the RAM-model MPC setting, seemingly putting an epilogue in the theory of ORAM. In this paper, we initiate a study of mixed-mode ORAMs, where accesses...

In this work, we consider secure multiparty computation (MPC) in the asynchronous network setting. MPC allows $n$ parties to compute a public function on their private inputs against an adversary corrupting at most $t$ of them. We consider both communication complexity and round complexity of asynchronous MPC (AMPC) with the optimal resilience $n=3t+1$. Without fully homomorphic encryptions, the best-known result in this setting is achieved by Coretti, Garay, Hirt, and Zikas...

Collaborative zk-SNARKs (Ozdemir and Boneh, USENIX’22) are a multiparty variant of zk-SNARKs where multiple, mutually distrustful provers, each holding a private input, jointly compute a zk-SNARK using their combined inputs. A sequence of works has proposed efficient constructions of collaborative zk-SNARKs using a common template that involves designing secure multiparty computation (MPC) protocols to emulate a zk-SNARK prover without making non-black-box use of cryptography. To achieve...

Differentially private stochastic gradient descent (DP-SGD) trains machine learning (ML) models with formal privacy guarantees for the training set by adding random noise to gradient updates. In collaborative learning (CL), where multiple parties jointly train a model, noise addition occurs either (i) before or (ii) during secure gradient aggregation. The first option is deployed in distributed DP methods, which require greater amounts of total noise to achieve security, resulting in...

A long line of work has investigated the design of scalable secure multiparty computation (MPC) protocols with computational and communication complexity independent of the number of parties (beyond any dependence on the circuit size). We present the first unconditionally-secure MPC protocols for arithmetic circuits over {\em large fields} with total computation $\mathcal{O}(|C|\log|F|)$, where $|C|$ and $|F|$ denote the circuit and field size, respectively. Prior work could either...

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...

The LowMC-based post-quantum signature scheme Picnic was selected as a third-round candidate for NIST PQC, attracting wide attention to the design of efficient and secure post-quantum signature schemes using Symmetric Techniques for Advanced Protocols (STAP). Symmetric primitives designed for advanced protocols such as secure multi-party computation (MPC), fully homomorphic encryption (FHE), and zero-knowledge (ZK) proof systems, with the goal of reducing the number of multiplication...

In TCC 2018, Boneh, Ishai, Passelègue, Sahai, and Wu propose candidates of weak and strong PRFs by evaluating linear functions over coprime moduli alternatively. Such PRFs can be evaluated by low-depth circuits and are MPC-friendly. However, they have not been able to base the security of their PRFs on well-formed assumptions other than assuming that the PRF constructions themselves are secure. In this paper, we formalize a new assumption called Learning with Alternating Moduli (LAM)....

Multiparty fully homomorphic encryption (MPFHE) is a generalization of (multi-key) fully homomorphic encryption ((MK)FHE) that lives on the cusp between multiparty computation (MPC) and FHE, enabling a computation over encrypted data using multiple keys. However, contrary to MKFHE it seeks to reduce the noise inflation based on the number of parties by allowing the parties to first compute shared data in MPC before executing the computation in FHE. Generally, MPFHE protocols have required...

Threshold linearly homomorphic encryption (ThLHE) is a useful cryptographic tool for secure computation in multi-party settings, with applications in electronic voting, secure multiparty computation (MPC), and beyond. Although ThLHE offers significant advantages such as low communication overhead, its adoption in modern systems is hindered by a critical dilemma between efficiency and utility. Precisely, existing ThLHE schemes either suffer from high decryption complexity—typically...

Secure Multi-Party Computation (MPC) allows multiple parties to perform privacy-preserving computation on their secret data. MPC protocols based on secret sharing have high throughput which makes them well-suited for batch processing, where multiple instances are evaluated in parallel. So far, practical implementations of secret sharing-based MPC protocols mainly focus on runtime and communication efficiency, so the memory overhead of protocol implementations is often overlooked....

Private set intersection (PSI) is a well-researched cryptographic primitive that allows two parties to compute the intersection of their input sets without revealing any information about items outside of the intersection. Fuzzy private set intersection is a relatively new variant of PSI, where items are not matched exactly but ``fuzzily''. Most commonly, items are points $\mathbf{q},\mathbf{w}$ in $d$-dimensional integer space $\mathbb{Z}^d$ and a point is a fuzzy match to another if it...

Secure multiparty computation (MPC) allows data owners to train machine learning models on combined data while keeping the underlying training data private. The MPC threat model either considers an adversary who passively corrupts some parties without affecting their overall behavior, or an adversary who actively modifies the behavior of corrupt parties. It has been argued that in some settings, active security is not a major concern, partly because of the potential risk of reputation loss...

Blind signature schemes are essential for privacy-preserving applications such as electronic voting, digital currencies or anonymous credentials. In this paper, we revisit Fischlin's framework for round-optimal blind signature schemes and its recent efficient lattice-based instantiations. Our proposed framework compiles any post-quantum hash-and-sign signature scheme into a blind signature scheme. The resulting scheme ensures blindness by design and achieves one-more unforgeability, relying...

In key-and-message homomorphic encryption (KMHE), the key space is a subset of the message space, allowing encryption of secret keys such that the same homomorphism can be applied to both the key and the message of a given ciphertext. KMHE with suitable security properties is the main building block for constructing rerandomizable garbling schemes (RGS, Gentry et al., CRYPTO 2010), which enable advanced cryptographic applications like multi-hop homomorphic encryption, the YOSO-like MPC...

Threshold ECDSA schemes distribute the capability of issuing signatures to multiple parties. They have been used in practical MPC wallets holding cryptocurrencies. However, most prior protocols are not robust, wherein even one misbehaving or non-responsive party would mandate an abort. Robust schemes have been proposed (Wong et al., NDSS ’23, ’24), but they do not match state-of-the-art number of rounds which is only three (Doerner et al., S&P ’24). In this work, we propose robust threshold...

SPDZ-style and BMR-style protocols are widely known as practical MPC protocols that achieve active security in the dishonest majority setting. However, to date, SPDZ-style protocols have not achieved constant rounds, and BMR-style protocols have struggled to achieve scalable communication or computation. Additionally, there exists fully homomorphic encryption (FHE)-based MPC protocols that achieve both constant rounds and scalable communication, but they face challenges in achieving active...

There is rising interest in combining Differential Privacy (DP) and Secure Multiparty Computation (MPC) techniques to protect distributed database query evaluations from both adversaries taking part in the computation and those observing the outputs. This requires implementing both the query evaluation and noise generation parts of a DP mechanism directly in MPC. While query evaluation can be done using existing highly optimized MPC techniques for secure function evaluation, efficiently...

Many user-centric applications face a common privacy problem: the need to collect, store, and analyze sensitive user data. Examples include check-in/check-out based payment systems for public transportation, charging/discharging electric vehicle batteries in smart grids, coalition loyalty programs, behavior-based car insurance, and more. We propose and evaluate a generic solution to this problem. More specifically, we provide a formal framework integrating privacy-preserving data collection,...

AES has cemented its position as the primary symmetric-key primitive for a wide range of cryptographic applications, which motivates the analysis on the concrete security of AES in practical instantiations, for instance, the collision resistance of AES-based hashing, the key commitment security of AES-based authenticated encryption schemes, and the one-wayness of AES-based one-way functions in ZK and MPC protocols. In this work, we introduce single-color initial structures (SCIS) into...

Secure multi-party computation (MPC) enables parties to compute a function over private inputs while maintaining confidentiality. Although MPC has advanced significantly and attracts a growing industry interest, open-source implementations are still at an early stage, with no production-ready code and a poor understanding of their actual security guarantees. In this work, we study the real-world security of modern MPC implementations, focusing on the SPDZ protocol (Damgård et al., CRYPTO...

We put forth a new paradigm for practical secure multiparty 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...

In this work, we present an efficient secure multi-party computation MPC protocol that provides strong security guarantees in settings with a dishonest majority of participants who may behave arbitrarily. Unlike the popular MPC implementation known as SPDZ [Crypto ’12], which only ensures security with abort, our protocol achieves both complete identifiability and robustness. With complete identifiability, honest parties can detect and unanimously agree on the identity of any malicious...

Generic Secure Multiparty Computation (Generic MPC) recently received much attraction in the blockchain realm as it allows mutually distrustful parties to jointly compute a global function using their private inputs while keeping them private; and more so; the expression of the function can be done in a programmable manner (hence `generic'); as opposed to the first rising star cryptographic technique Zero-Knowledge Proof (ZKP) which only allows computation on private input of a single party...

Threshold public-key encryption securely distributes private key shares among multiple participants, requiring a minimum number of them to decrypt messages. We introduce a quantum-resistant threshold public-key encryption scheme based on the code-based Niederreiter cryptosystem that achieves security against chosen ciphertext attacks. A previous attempt was made recently by Takahashi, Hashimoto, and Ogata (published at DCC in 2023) but we show that it contains a critical security flaw that...

The major Fully Homomorphic Encryption (FHE) schemes guarantee the privacy of the encrypted message only in the honest-but-curious setting, when the server follows the protocol without deviating. However, various attacks in the literature show that an actively malicious server can recover sensitive information by executing incorrect functions, tampering with ciphertexts, or observing the client’s reaction during decryption. Existing integrity solutions for FHE schemes either fail to...

This document is a preliminary version of what is intended to be submitted to NIST by Zama as part of their threshold call. The document also serves as partial documentation of the protocols used in the Zama MPC system for threshold TFHE. However, note that the Zama software includes many optimizations built on top of the simple specifications given here. In particular the TFHE parameters given here are larger than those used by the Zama software. This is because the Zama TFHE library...

In this paper, we present Trilithium: a protocol for distributed key generation and signing compliant with FIPS 204 (ML-DSA). Our protocol allows two parties, "server" and "phone" with assistance of correlated randomness provider (CRP) to produce a standard ML-DSA signature. We prove our protocol to be secure against a malicious server or phone in the universal composability (UC) model, introducing some novel techniques to argue the security of two-party secure computation protocols with...

Generalized secret sharing (GSS) enables flexible access control in distributed systems by allowing secrets to be shared across arbitrary monotone access structures. However, its adoption in transparent and trustless environments is hindered due to the reliance on trusted participants and secure communication channels. This reliance restricts GSS's ability to provide flexible control in the presence of adversaries. In this paper, we propose publicly verifiable generalized secret sharing...

The increased popularity of large language models (LLMs) raises serious privacy concerns, where users' private queries are sent to untrusted servers. Many cryptographic techniques have been proposed to provide privacy, such as secure multiparty computation (MPC), which enables the evaluation of LLMs directly on private data. However, cryptographic techniques have been deemed impractical as they introduce large communication and computation. On the other hand, many obfuscation techniques have...

Typical protocols in the multi-party private set operations (MPSO) setting enable $m > 2$ parties to perform certain secure computation on the intersection or union of their private sets, realizing a very limited range of MPSO functionalities. Most works in this field focus on just one or two specific functionalities, resulting in a large variety of isolated schemes and a lack of a unified framework in MPSO research. In this work, we present an MPSO framework, which allows $m$ parties, each...

The YOSO (You Only Speak Once) model, introduced by Gentry et al. (CRYPTO 2021), helps to achieve strong security guarantees in cryptographic protocols for distributed settings, like blockchains, with large number of parties. YOSO protocols typically employ smaller anonymous committees to execute individual rounds of the protocol instead of having all parties execute the entire protocol. After completing their tasks, parties encrypt protocol messages for the next anonymous committee and...

Secure graph computation enables computing on graphs while hiding the graph topology as well as the associated node/edge data. This facilitates collaborative analysis among multiple data owners, who may only hold a private partial view of the global graph. Several works address this problem using the technique of secure multiparty computation (MPC) in the presence of 2 or 3 parties. However, when moving to the multiparty setting, as required for collaborative analysis among multiple data...

Side-channel attacks pose significant threats to cryptographic implementations, which require the inclusion of countermeasures to mitigate these attacks. In this work, we study the masking of state-of-the-art post-quantum signatures based on the MPC-in-the-head paradigm. More precisely, we focus on the recent threshold-computation-in-the-head (TCitH) framework that applies to some NIST candidates of the post-quantum standardization process. We first provide an analysis of side-channel attack...

In this work, we study the communication complexity of constant-round secure multiparty computation (MPC) against a fully malicious adversary and consider both the honest majority setting and the dishonest majority setting. In the (strong) honest majority setting (where $t=(1/2-\epsilon)n$ for a constant $\epsilon$), the best-known result without relying on FHE is given by Beck et al. (CCS 2023) based on the LPN assumption that achieves $O(|C|\kappa)$ communication, where $\kappa$ is the...

Multi-party computation (MPC) has become increasingly practical in the last two decades, solving privacy and security issues in various domains, such as healthcare, finance, and machine learning. One big caveat is that MPC sometimes lacks usability since the knowledge barrier for regular users can be high. Users have to deal with, e.g., various CLI tools, private networks, and sometimes even must install many dependencies, which are often hardware-dependent. A solution to improve the...

The most fundamental performance metrics of secure multi-party computation (MPC) protocols are related to the number of messages the parties exchange (i.e., round complexity), the size of these messages (i.e., communication complexity), and the overall computational resources required to execute the protocol (i.e., computational complexity). Another quality metric of MPC protocols is related to the black-box or non-black-box use of the underlying cryptographic primitives. Indeed, the design...

This paper examines the deployment of Multi-Party Computation (MPC) in corporate data processing environments, focusing on its legal and technical implications under the European Union’s General Data Protection Regulation (GDPR). By combining expertise in cryptography and legal analysis, we address critical questions necessary for assessing the suitability of MPC for real-world applications. Our legal evaluation explores the conditions under which MPC qualifies as an anonymizing approach...

Generative models have achieved remarkable success in a wide range of applications. Training such models using proprietary data from multiple parties has been studied in the realm of federated learning. Yet recent studies showed that reconstruction of authentic training data can be achieved in such settings. On the other hand, multiparty computation (MPC) guarantees standard data privacy, yet scales poorly for training generative models. In this paper, we focus on improving...

Oblivious permutation (OP) enables two parties, a sender with a private data vector $x$ and a receiver with a private permutation π, to securely obtain the shares of π(x). OP has been used to construct many important MPC primitives and applications such as secret shuffle, oblivious sorting, private set operations, secure database analysis, and privacy-preserving machine learning. Due to its high complexity, OP has become a performance bottleneck in several practical applications, and many...

State-of-the-art protocols that achieve constant-round secure multiparty computation currently present a trade-off: either consume an amount of communication that scales quadratically in the number of parties, or achieve better asymptotics at the cost of high constant factors (e.g. schemes based on LPN or DDH). We construct a constant-round MPC protocol where communication scales linearly in the number of parties n. Our construction relies only on OT and RO, and it leverages packed...

This note demonstrates that the blind signature scheme based on cryptographic group actions, as proposed in ePrint paper 2025/397, fails to ensure blindness. Specifically, we construct an adversary that achieves a $1/8$ advantage in the blindness experiment. The attack leverages selective abort techniques (also known as selective failure attacks), a well-known strategy in the MPC literature.

Private computation on common records refers to analyze data from two databases containing shared records without revealing personal information. As a basic requirement for private computation, the databases involved essentially need to be aligned by a common identification system. However, it is hard to expect such common identifiers in real world scenario. For this reason, multiple quasi-identifiers can be used to identify common records. As some quasi-identifiers might be missing or have...

The introduction of shared computation architectures assembled from heterogeneous chiplets introduces new security threats. Due to the shared logical and physical resources, an untrusted chiplet can act maliciously to surreptitiously probe the data communication between chiplets or sense the computation shared between them. This paper presents Garblet, the first framework to leverage the flexibility offered by chiplet technology and Garbled Circuits (GC)-based MPC to enable efficient,...

Threshold fully homomorphic encryption (ThFHE) is an extension of FHE that can be applied to multiparty computation (MPC) with low round complexity. Recently, Passelègue and Stehlé (Asiacrypt 2024) presented a simulation-secure ThFHE scheme with polynomially small decryption shares from “yet another” learning with errors assumption (LWE), in which the norm of the secret key is leaked to the adversary. While “yet another” LWE is reduced from standard LWE, its module variant, “yet another”...

In this paper, we present the first practical algorithm to compute an effective group action of the class group of any imaginary quadratic order $\mathcal{O}$ on a set of supersingular elliptic curves primitively oriented by $\mathcal{O}$. Effective means that we can act with any element of the class group directly, and are not restricted to acting by products of ideals of small norm, as for instance in CSIDH. Such restricted effective group actions often hamper cryptographic constructions,...

Secure multi-party computation (MPC) enables collaborative, privacy-preserving computation over private inputs. Advances in homomorphic encryption (HE), particularly the CKKS scheme, have made secure computation practical, making it well-suited for real-world applications involving approximate computations. However, the inherent approximation errors in CKKS present significant challenges in developing MPC protocols. This paper investigates the problem of secure approximate MPC from CKKS....

In this work, we consider the setting where the process of securely evaluating a multi-party functionality is divided into two phases: offline (or preprocessing) and online. The offline phase is independent of the parties’ inputs, whereas the online phase does require the knowledge of the inputs. We consider the problem of minimizing the round of communication required in the online phase and propose a round preserving compiler that can turn a big class of multi-party computation (MPC)...

We study efficient public randomness generation protocols in the PASSO (PArties Speak Sequentially Once) model for multi-party computation (MPC). PASSO is a variation of traditional MPC where $n$ parties are executed in sequence and each party ``speaks'' only once, broadcasting and sending secret messages only to parties further down the line. Prior results in this setting include information-theoretic protocols in which the computational complexity scales exponentially with the number of...

In Crypto'19, Goyal, Jain, and Sahai (GJS) introduced the elegant notion of *secret-sharing of an NP statement* (NPSS). Roughly speaking, a $t$-out-of-$n$ secret sharing of an NP statement is a reduction that maps an instance-witness pair to $n$ instance-witness pairs such that any subset of $(t-1)$ reveals no information about the original witness, while any subset of $t$ allows full recovery of the original witness. Although the notion was formulated for general $t \leq n$, the only...

Zero-Knowledge Succinct Non-interactive Arguments of Knowledge (zkSNARKs) lead to proofs that can be succinctly verified but require huge computational resources to generate. Prior systems outsource proof generation either through public delegation, which reveals the witness to the third party, or, more preferably, private delegation that keeps the witness hidden using multiparty computation (MPC). However, current private delegation schemes struggle with scalability and efficiency due to...

Syndrome decoding (SD), and equivalently Learning Parity with Noise (LPN), is a fundamental problem in cryptography, which states that for a field $\mathbb{F}$, some compressing public matrix $\mathbf{G} \in \mathbb{F}^{k\times n}$, and a secret sparse vector $\mathbf{e} \in\mathbb{F}^{n}$ sampled from some noise distribution, $\mathbf{G}\mathbf{e}$ is indistinguishable from uniform. Recently, the SD has gained significant interest due to its use in pseudorandom correlation generators...

In this work, we consider the communication complexity of MPC protocols in honest majority setting achieving malicious security in both information-theoretic setting and computational setting. On the one hand, we study the possibility of basing honest majority MPC protocols on oblivious linear evaluation (OLE)-hybrid model efficiently with information-theoretic security. More precisely, we instantiate preprocessing phase of the recent work Sharing Transformation (Goyal, Polychroniadou, and...

Secure computation enables mutually distrusting parties to jointly compute a function on their secret inputs, while revealing nothing beyond the function output. A long-running challenge is understanding the required communication complexity of such protocols – in particular, when communication can be sublinear in the circuit representation size of the desired function. While several techniques have demonstrated the viability of sublinear secure computation in the two-party setting, known...

Publicly identifiable abort is a critical feature for ensuring accountability in outsourced computations using secure multiparty computation (MPC). Despite its importance, no prior work has specifically addressed identifiable abort in the context of outsourced computations. In this paper, we present the first MPC protocol that supports publicly identifiable abort with minimal overhead for external clients. Our approach minimizes client-side computation by requiring only a few pseudorandom...

We study the round-complexity of secure multi-party computation (MPC) in the post-quantum regime where honest parties and communication channels are classical but the adversary can be a quantum machine. Our focus is on the $\mathit{fully}$ black-box setting where both the construction as well as the security reduction are black-box in nature. In this context, Chia, Chung, Liu, and Yamakawa [FOCS'22] demonstrated the infeasibility of achieving standard simulation-based security within...

We introduce a general template for building garbled circuits with low communication, under the decisional composite residuosity (DCR) assumption. For the case of layered Boolean circuits, we can garble a circuit of size $s$ with communication proportional to $O(s/\log\log s)$ bits, plus an additive factor that is polynomial in the security parameter. For layered arithmetic circuits with $B$-bounded integer computation, we obtain a similar result: the garbled arithmetic circuit has size...

This paper introduces a decentralized and leaderless sealed bid auction model for dynamic pricing of intents across blockchain networks. We leverage Multi-Party Computation (MPC) and Identity-Based Encryption (IBE) to improve pricing while ensuring fairness and decentralization. By addressing the vulnerabilities of current centralized or static pricing mechanisms, our approach fosters transparent, secure, and competitive price discovery. We further enhance the confidentiality of intents...

Can a sender commit to a long input without even reading all of it? Can a prover convince a verifier that an NP statement holds without even reading the entire witness? Can a set of parties run a multiparty computation (MPC) protocol in the RAM model, without necessarily even reading their entire inputs? We show how to construct such "doubly efficient" schemes in a setting where parties can preprocess their input offline, but subsequently they can engage in many different protocol...

Network agnostic protocols (Blum, Katz, Loss TCC `19) are consensus or MPC protocols that strike a balance between purely synchronous and asynchronous protocols. Given thresholds $t_a,t_s$ that satisfy $t_a<n/3<t_s<n/2$ and $2t_s+t_a<n$, they have the unique property of remaining secure against an adversary that either (1) corrupts up to $t_s$ parties in a synchronous execution where all messages are delivered within a known bound $\Delta$ or (2) corrupts up to $t_a$ in an asynchronous...

It is often desirable to break cryptographic primitives into two components: an input-independent offline component, and a cheap online component used when inputs arrive. Security of such online/offline primitives must be proved in the input-adaptive setting: the adversary chooses its input adaptively, based on what it sees in the offline-phase. Proving security in the input-adaptive setting can be difficult, particularly when one wishes to achieve simulation security and avoid idealized...

Lund et al. (JACM 1992) invented the powerful Sumcheck protocol that has been extensively used in complexity theory and in designing concretely efficient (zero-knowledge) arguments. In this work, we systematically study Sumcheck in the context of secure multi-party computation (MPC). Our main result is a new generic framework for lifting semi-honest MPC protocols to maliciously secure ones, with a {\em constant} multiplicative overhead in {\em both} computation and communication, and in the...

Correlated randomness lies at the core of efficient modern secure multi-party computation (MPC) protocols. Costs of generating such correlated randomness required for the MPC online phase protocol often constitute a bottleneck in the overall protocol. A recent paradigm of {\em pseudorandom correlation generator} (PCG) initiated by Boyle et al. (CCS'18, Crypto'19) offers an appealing solution to this issue. In sketch, each party is given a short PCG seed, which can be locally expanded into...

In this paper, we revisit shuffle protocol for Shamir secret sharing. Upon examining previous works, we observe that existing constructions either produce non-uniform shuffle or require large communication and round complexity, e.g. exponential in the number of parties. We propose two shuffle protocols, both of which shuffle uniformly within $O(\frac{k + l}{\log k}n^2m\log m)$ communication for shuffling rows of an $m\times l$ matrix shared among $n$ parties, where $k\leq m$ is a parameter...

Private Join and Compute (PJC) is a two-party protocol recently proposed by Google for various use-cases, including ad conversion (Asiacrypt 2021) and which generalizes their deployed private set intersection sum (PSI-SUM) protocol (EuroS&P 2020). PJC allows two parties, each holding a key-value database, to privately evaluate the inner product of the values whose keys lie in the intersection. While the functionality output is not typically considered in the security model of the MPC...

We present the first complete adaptively secure asynchronous MPC protocol for the YOSO (You Speak Only Once) setting. In contrast to many previous MPC constructions in the YOSO model, we provide a full stack implementation that does MPC, role assignment and total order broadcast. Therefore, our construction is also the first to provide adaptively secure asynchronous total order broadcast and MPC that is sub-quadratic in the number of parties and does not require threshold fully homomorphic...

Introduced by Halevi, Ishai, Kushilevitz, and Rabin (CRYPTO 2023), Additive randomized encodings (ARE) reduce the computation of a $k$-party function $f(x_1,\dots,x_k)$ to locally computing encodings $\hat x_i$ of each input $x_i$ and then adding them together over some Abelian group into an output encoding $\hat y = \sum \hat x_i$, which reveals nothing but the result. The appeal of ARE comes from the simplicity of the non-local computation, involving only addition. This gives rise for...

We put forth and instantiate a new primitive we call simultaneous-message and succinct (SMS) secure computation. An SMS scheme enables a minimal communication pattern for secure computation in the following scenario: Alice has a large private input X, Bob has a small private input y, and Charlie wants to learn $f(X, y)$ for some public function $f$. Given a common reference string (CRS) setup phase, an SMS scheme for a function f is instantiated with two parties holding inputs $X$ and...

Homomorphic secret sharing (HSS) is a distributed analogue of fully homomorphic encryption (FHE) where following an input-sharing phase, two or more parties can locally compute a function over their private inputs to obtain shares of the function output. Over the last decade, HSS schemes have been constructed from an array of different assumptions. However, all existing HSS schemes, except ones based on assumptions known to imply multi-key FHE, require a public-key infrastructure (PKI) or...

Multiparty computation (MPC) allows a set of mutually distrusting parties to compute a function over their inputs, while keeping those inputs private. Most recent MPC protocols that are ready for real-world applications are based on the so-called preprocessing model, where the MPC is split into two phases: a preprocessing phase, where raw material, independent of the inputs, is produced; and an online phase, which can be efficiently computed, consuming this preprocessed material, when the...

Secure Multiparty Computation (MPC) protocols that achieve Identifiable Abort (IA) guarantee honest parties that in the event that they are denied output, they will be notified of the identity of at least one corrupt party responsible for the abort. Cheater identification provides recourse in the event of a protocol failure, and in some cases can even be desired over Guaranteed Output Delivery. However, protocols in the literature typically make use of broadcast as a necessary tool in...

Verifiable random access machines (vRAMs) serve as a foundational model for expressing complex computations with provable security guarantees, serving applications in areas such as secure electronic voting, financial auditing, and privacy-preserving smart contracts. However, no existing vRAM provides distributed obliviousness, a critical need in scenarios where multiple provers seek to prevent disclosure against both other provers and the verifiers. Implementing a publicly verifiable...

The server-aided model for multiparty computation (MPC) was introduced to capture a real-world scenario where clients wish to off-load the heavy computation of MPC protocols to dedicated servers. A rich body of work has studied various trade-offs between security guarantees (e.g., semi-honest vs malicious), trust assumptions (e.g., the threshold on corrupted servers), and efficiency. However, all existing works make the assumption that all clients must agree on employing the same...

In recent development of secure multi-party computation (MPC), pseudorandom correlations of subfield vector oblivious linear evaluation (sVOLE) type become popular due to their amazing applicability in multi-dimensional MPC protocols such as privacy-preserving biometric identification and privacy-preserving machine learning protocols. In this paper, we introduce a novel way of VOLE distribution in three-party and four-party honest majority settings with the aid of a trusted server. This new...

Today, many auctions are carried out with the help of intermediary platforms like Google and eBay. These platforms serve as a rendezvous point for the buyers and sellers, and charge a fee for its service. We refer to such auctions as platform-assisted auctions. Traditionally, the auction theory literature mainly focuses on designing auctions that incentivize the buyers to bid truthfully, assuming that the platform always faithfully implements the auction. In practice, however, the platforms...

This paper introduces new protocols for secure multiparty computation (MPC) leveraging Discrete Wavelet Transforms (DWTs) for computing nonlinear functions over large domains. By employing DWTs, the protocols significantly reduce the overhead typically associated with Lookup Table-style (LUT) evaluations in MPC. We state and prove foundational results for DWT-compressed LUTs in MPC, present protocols for 9 of the most common activation functions used in ML, and experimentally evaluate the...

Secure multi-party computation (MPC) is a crucial tool for privacy-preserving computation, but it is getting increasingly complicated due to recent advancements and optimizations. Programming tools for MPC allow programmers to develop MPC applications without mastering all cryptography. However, most existing MPC programming tools fail to attract real users due to the lack of documentation, maintenance, and the ability to compose with legacy codebases. In this work, we build Smaug, a modular...

The \emph{Fluid} multiparty computation (MPC) model, introduced in (Choudhuri \emph{et al.} CRYPTO 2021), addresses dynamic scenarios where participants can join or leave computations between rounds. Communication complexity initially stood at $\Omega(n^2)$ elements per gate, where $n$ is the number of parties in a committee online at a time. This held for both statistical security (honest majority) and computational security (dishonest majority) in (Choudhuri \emph{et al.}~CRYPTO'21) and...

A partial key exposure attack is a key recovery attack where an adversary obtains a priori partial knowledge of the secret key, e.g., through side-channel leakage. While for a long time post-quantum cryptosystems, unlike RSA, have been believed to be resistant to such attacks, recent results by Esser, May, Verbel, and Wen (CRYPTO ’22), and by Kirshanova and May (SCN ’22), have refuted this belief. In this work, we focus on partial key exposure attacks in the context of rank-metric-based...

Cleve (STOC 86) shows that an honest majority is necessary for MPC with guaranteed output delivery. In this paper, we show that while an honest majority is indeed necessary, its involvement can be minimal. We demonstrate an MPC protocol with guaranteed output delivery, the majority of which is executed by a sequence of committees with dishonest majority; we leverage one committee with an honest majority, each member of which does work independent of the circuit size. Our protocol has the...

The growing adoption of secure multi-party computation (MPC) has driven the development of efficient symmetric key primitives tailored for MPC. Recent advances, such as the alternating moduli paradigm, have shown promise but leave room for cryptographic and practical improvements. In this paper, we analyze a family of weak pseudorandom functions (wPRF) proposed at Crypto 2024, focusing on their One-to-One parameter sets. We demonstrate that these configurations fail to achieve their intended...

Multilateral Trade Credit Set-off (MTCS) is a process run by a service provider that collects trade credit data (i.e. obligations from a firm to pay another firm) from a network of firms and detects cycles of debts that can be removed from the system. The process yields liquidity savings for the participants, who can discharge their debts without relying on expensive loans. We propose an MTCS protocol that protects firms' sensitive data, such as the obligation amount or the identity of the...

We present an efficient and simple multi-party private set intersection cardinality (PSI-CA) protocol that allows several parties to learn the intersection size of their private sets without revealing any other information. Our protocol is highly efficient because it only utilizes the Oblivious Key-Value Store and zero-sharing techniques, without incorporating components such as OPPRF (Oblivious Programmable Pseudorandom Function) which is the main building block of multi-party PSI-CA...

Private Set Intersection (PSI) is a cryptographic primitive that allows two parties to obtain the intersection of their private input sets while revealing nothing more than the intersection. PSI and its numerous variants, which compute on the intersection of items and their associated weights, have been widely studied. In this paper, we revisit the problem of finding the best item in the intersection according to weight sum introduced by Beauregard et al. (SCN '22), which is a special...

Fixed Point Arithmetic (FPA) is widely used in Privacy-Preserving Machine Learning (PPML) to efficiently handle decimal values. However, repeated multiplications in FPA can lead to overflow, as the fractional part doubles in size with each multiplication. To address this, truncation is applied post-multiplication to maintain precision. Various truncation schemes based on Secure Multiparty Computation (MPC) exist, but trade-offs between accuracy and efficiency in PPML models and datasets...

We introduce the linear-transformation model, a distributed model of differentially private data analysis. Clients have access to a trusted platform capable of applying a public matrix to their inputs. Such computations can be securely distributed across multiple servers using simple and efficient secure multiparty computation techniques. The linear-transformation model serves as an intermediate model between the highly expressive central model and the minimal local model. In the central...

Shuffle is a frequently used operation in secure multiparty computations, with applications including joint data analysis, anonymous communication systems, secure multiparty sorting, etc. Despite a series of ingenious works, the online (i.e. data-dependent) complexity of malicious secure $n$-party shuffle protocol remains $\Omega(n^2m)$ for shuffling data array of length $m$. This potentially slows down the application and MPC primitives built upon MPC shuffle. In this paper, we...

We investigate the feasibility of constructing threshold signature schemes from the MPC-in-the-head paradigm. Our work addresses the significant challenge posed by recent impossibility results (Doerner et al., Crypto’24), which establish inherent barriers to efficient thresholdization of such schemes without compromising their security or significantly increasing the signature size. - We introduce a general methodology to adapt any MPC-in-the-head signature into a threshold-friendly...

In this paper, we present the first single trace side-channel attack that targets the MPC-in-the-Head (MPCitH) framework based on threshold secret sharing, also known as Threshold Computation in the Head (TCitH) in its original version. This MPCitH framework can be found in 5 of the 14 digital signatures schemes in the recent second round of the National Institute of Standards and Technology (NIST) call for digital signatures. In this work, we start by highlighting a side-channel...

As privacy concerns have arisen in machine learning, privacy-preserving machine learning (PPML) has received significant attention. Fully homomorphic encryption (FHE) and secure multi-party computation (MPC) are representative building blocks for PPML. However, in PPML protocols based on FHE and MPC, interaction between the client (who provides encrypted input data) and the evaluator (who performs the computation) is essential to obtain the final result in plaintext. Functional encryption...

We present a new construction of two-party, threshold ECDSA, building on a 2017 scheme of Lindell and improving his scheme in several ways. ECDSA signing is notoriously hard to distribute securely, due to non-linearities in the signing function. Lindell's scheme uses Paillier encryption to encrypt one party's key share and handle these non-linearities homomorphically, while elegantly avoiding any expensive zero knowledge proofs over the Paillier group during the signing process. However,...

Succinct randomized encodings allow encoding the input $x$ of a time-$t$ uniform computation $M(x)$ in sub-linear time $o(t)$. The resulting encoding $\tilde{x}$ allows recovering the result of the computation $M(x)$, but hides any other information about $x$. These encodings have powerful applications, including time-lock puzzles, reducing communication in MPC, and bootstrapping advanced encryption schemes. Until not long ago, the only known constructions were based on...

In this paper we introduce the notion of encrypted RAM delegation. In an encrypted RAM delegation scheme, the prover creates a succinct proof for a group of two input strings $x_\mathsf{pb}$ and $x_\mathsf{pr}$, where $x_\mathsf{pb}$ corresponds to a large \emph{public} input and $x_\mathsf{pr}$ is a \emph{private} input. A verifier can check correctness of computation of $\mathcal{M}$ on $(x_\mathsf{pb}, x_\mathsf{pr})$, given only the proof $\pi$ and $x_\mathsf{pb}$. We design encrypted...

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive, in which a prover convinces a verifier that a given statement is true without leaking any additional information. However, existing zkSNARKs suffer from high computation overhead in the proof generation. This limits the applications of zkSNARKs, such as private payments, private smart contracts, and anonymous credentials. Private delegation has become a prominent way to accelerate...

We propose a privacy-preserving multiparty search protocol using threshold-level homomorphic encryption, which we prove correct and secure to honest but curious adversaries. Unlike existing approaches, our protocol maintains a constant circuit depth. This feature enhances its suitability for practical applications involving dynamic underlying databases.