Multi-party computation (MPC) enables a set of mutually n distrusting parties to compute any function on their private inputs. Mainly, MPC facilitates agreement on the function's output while preserving the secrecy of honest inputs, even against a subset of t parties controlled by an adversary. With applications spanning from anonymous broadcast to private auctions, MPC is considered a cornerstone of distributed cryptography, and significant research efforts have been aimed at making MPC practical in the last decade. However, most libraries either make strong assumptions like the network being bounded synchronous, or incur high computation overhead from the extensive use of expensive public-key operations that prevent them from scaling beyond a few dozen parties. This work presents Velox, an asynchronous MPC protocol that offers fairness against an optimal adversary corrupting up to t < n/3 parties. Velox significantly enhances practicality by leveraging lightweight cryptographic primitives-such as symmetric-key encryption and hash functions-which are 2-3 orders of magnitude faster than public-key operations, resulting in substantial computational efficiency. Moreover, Velox is highly communication-efficient, with linear amortized communication relative to circuit size and only O(n3) field elements of additive overhead. Concretely, Velox requires just 9.33 field elements per party per multiplication gate, more than 10× reduction compared to the state of the art. Moreover, Velox also offers Post-Quantum Security as lightweight cryptographic primitives retain their security against a quantum adversary. We implement Velox comprehensively, covering both offline and online phases, and evaluate its performance on a geographically distributed testbed through a real-world application: anonymous broadcast. Our implementation securely shuffles a batch of k = 256 messages in 4 seconds with n = 16 parties and 18 seconds with n = 64 parties, a 36× and 28.6× reduction in latency compared to the prior best work. At scale with n = 112 parties, Velox is able to shuffle the same batch of messages in under 50 seconds from end to end, illustrating its effectiveness and scalability. Overall, our work removes significant barriers faced by prior asynchronous MPC solutions, making asynchronous MPC practical and efficient for large-scale deployments involving 100s of parties.
Multi-party computation (MPC) enables a set of mutually n distrusting parties to compute any function on their private inputs. Mainly, MPC facilitates agreement on the function's output while preserving the secrecy of honest inputs, even against a subset of t parties controlled by an adversary. With applications spanning from anonymous broadcast to private auctions, MPC is considered a cornerstone of distributed cryptography, and significant research efforts have been aimed at making MPC practical in the last decade. However, most libraries either make strong assumptions like the network being bounded synchronous, or incur high computation overhead from the extensive use of expensive public-key operations that prevent them from scaling beyond a few dozen parties. This work presents Velox, an asynchronous MPC protocol that offers fairness against an optimal adversary corrupting up to t < n/3 parties. Velox significantly enhances practicality by leveraging lightweight cryptographic primitives-such as symmetric-key encryption and hash functions-which are 2-3 orders of magnitude faster than public-key operations, resulting in substantial computational efficiency. Moreover, Velox is highly communication-efficient, with linear amortized communication relative to circuit size and only O(n3) field elements of additive overhead. Concretely, Velox requires just 9.33 field elements per party per multiplication gate, more than 10× reduction compared to the state of the art. Moreover, Velox also offers Post-Quantum Security as lightweight cryptographic primitives retain their security against a quantum adversary. We implement Velox comprehensively, covering both offline and online phases, and evaluate its performance on a geographically distributed testbed through a real-world application: anonymous broadcast. Our implementation securely shuffles a batch of k = 256 messages in 4 seconds with n = 16 parties and 18 seconds with n = 64 parties, a 36× and 28.6× reduction in latency compared to the prior best work. At scale with n = 112 parties, Velox is able to shuffle the same batch of messages in under 50 seconds from end to end, illustrating its effectiveness and scalability. Overall, our work removes significant barriers faced by prior asynchronous MPC solutions, making asynchronous MPC practical and efficient for large-scale deployments involving 100s of parties.
Multi-party computation (MPC) enables a set of mutually n distrusting parties to compute any function on their private inputs. Mainly, MPC facilitates agreement on the function's output while preserving the secrecy of honest inputs, even against a subset of t parties controlled by an adversary. With applications spanning from anonymous broadcast to private auctions, MPC is considered a cornerstone of distributed cryptography, and significant research efforts have been aimed at making MPC practical in the last decade. However, most libraries either make strong assumptions like the network being bounded synchronous, or incur high computation overhead from the extensive use of expensive public-key operations that prevent them from scaling beyond a few dozen parties. This work presents Velox, an asynchronous MPC protocol that offers fairness against an optimal adversary corrupting up to t < n/3 parties. Velox significantly enhances practicality by leveraging lightweight cryptographic primitives-such as symmetric-key encryption and hash functions-which are 2-3 orders of magnitude faster than public-key operations, resulting in substantial computational efficiency. Moreover, Velox is highly communication-efficient, with linear amortized communication relative to circuit size and only O(n3) field elements of additive overhead. Concretely, Velox requires just 9.33 field elements per party per multiplication gate, more than 10× reduction compared to the state of the art. Moreover, Velox also offers Post-Quantum Security as lightweight cryptographic primitives retain their security against a quantum adversary. We implement Velox comprehensively, covering both offline and online phases, and evaluate its performance on a geographically distributed testbed through a real-world application: anonymous broadcast. Our implementation securely shuffles a batch of k = 256 messages in 4 seconds with n = 16 parties and 18 seconds with n = 64 parties, a 36× and 28.6× reduction in latency compared to the prior best work. At scale with n = 112 parties, Velox is able to shuffle the same batch of messages in under 50 seconds from end to end, illustrating its effectiveness and scalability. Overall, our work removes significant barriers faced by prior asynchronous MPC solutions, making asynchronous MPC practical and efficient for large-scale deployments involving 100s of parties.
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.
ulti-Party Computation (MPC) protocols allow a set of mutually distrustful parties to securely compute on their joint private inputs, maintaining the privacy of those.Since its early conception in the eighties, a plethora of research as well as some real world deployments have taken place, demonstrating the relevance of such an interesting mathematical problem.Nevertheless, most of the research and all deployments have focused on scenarios where both the number of parties and network latency are very low.This thesis lays out the first steps towards practical deployments of large-scale MPC, where many parties may be involved and they might only be connected through a high-latency network such as the Internet.Both theoretical and empirical evidence shows that non-constant-round protocols cannot perform well on slow networks for many functions.In order to overcome this issue, all the works in this thesis include concretely efficient constant-round protocols based on multi-party garbled circuits.Chapter 3 and Chapter 4 deal with the very strong setting where an active adversary corrupts all but one parties.The former achieves such goal by using homomorphic encryption for low-depth circuits.The latter, based on subsequent work, improves the theoretical understanding of the problem and utilises oblivious transfer to improve efficiency.In Chapter 5 we provide both constant and non-constant round protocols that can handle large numbers of parties more efficiently.We leverage our performance improvements by relaxing the setting where all but one parties are corrupted to one where a small minority of honest participants can be assumed.Concretely, such change allows to distribute secret key material so that each party only holds a 'short' part of the key.Security is then based on the concatenation of all honest parties' keys rather than on each party's individual key, improving both the communication and computation complexities.iii researcher.They would have not been the same without the support of family, friends and colleagues.I would like to start by thanking Nigel Smart for giving me this opportunity, being my advisor and introducing me to others in the community.Martijn Stam
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.
In this work, we study unconditionally-secure multi-party computation (MPC) tolerating t<n/3 corruptions, where n is the total number of parties involved. In this setting, it is well known that if the underlying network is completely asynchronous, then one can achieve only statistical security; moreover it is impossible to ensure input provision and consider inputs of all the honest parties. The best known statistically-secure asynchronous MPC (AMPC) with t<n/3 requires a communication of Ω(n5) field elements per multiplication. We consider a partially synchronous setting, where the parties are assumed to be globally synchronized initially for few rounds and then the network becomes completely asynchronous. In such a setting, we present a MPC protocol, which requires O(n2) communication per multiplication while ensuring input provision. Our MPC protocol relies on a new four round, communication efficient statistical verifiable secret-sharing (VSS) protocol with broadcast communication complexity independent of the number of secret-shared values.
We describe scalable protocols for solving the secure multi-party computation (MPC) problem among a large number of parties. We consider both the synchronous and the asynchronous communication models. In the synchronous setting, our protocol is secure against a static malicious adversary corrupting less than a 1/3 fraction of the parties. In the asynchronous setting, we allow the adversary to corrupt less than a 1/8 fraction of parties. For any deterministic function that can be computed by an arithmetic circuit with m gates, both of our protocols require each party to send a number of field elements and perform an amount of computation that is O~(m/n+n). We also show that our protocols provide perfect and universally-composable security. To achieve our asynchronous MPC result, we define the \emph{threshold counting problem} and present a distributed protocol to solve it in the asynchronous setting. This protocol is load balanced, with computation, communication and latency complexity of O(logn), and can also be used for designing other load-balanced applications in the asynchronous communication model.