In secure multi-party shuffling, multiple parties, each holding an input, want to agree on a random permutation of their inputs while keeping the permutation secret. This problem is important as a primitive in many privacy-preserving applications such as anonymous communication, location-based services, and electronic voting. Known techniques for solving this problem suffer from poor scalability, load-balancing issues, trusted party assumptions, and/or weak security guarantees. In this paper, we propose an unconditionally-secure protocol for multi-party shuffling that scales well with the number of parties and is load-balanced. In particular, we require each party to send only a polylogarithmic number of bits and perform a polylogarithmic number of operations while incurring only a logarithmic round complexity. We show security under universal compos ability against up to about n/3 fully-malicious parties. We also provide simulation results in the full version of this paper showing that our protocol improves significantly over previous work. For example, for one million parties, when compared to the state of the art, our protocol reduces the communication and computation costs by at least three orders of magnitude and slightly decreases the number of communication rounds.
In secure multi-party shuffling, multiple parties, each holding an input, want to agree on a random permutation of their inputs while keeping the permutation secret. This problem is important as a primitive in many privacy-preserving applications such as anonymous communication, location-based services, and electronic voting. Known techniques for solving this problem suffer from poor scalability, load-balancing issues, trusted party assumptions, and/or weak security guarantees. In this paper, we propose an unconditionally-secure protocol for multi-party shuffling that scales well with the number of parties and is load-balanced. In particular, we require each party to send only a polylogarithmic number of bits and perform a polylogarithmic number of operations while incurring only a logarithmic round complexity. We show security under universal compos ability against up to about n/3 fully-malicious parties. We also provide simulation results in the full version of this paper showing that our protocol improves significantly over previous work. For example, for one million parties, when compared to the state of the art, our protocol reduces the communication and computation costs by at least three orders of magnitude and slightly decreases the number of communication rounds.
Abstract. In secure multi-party shuffling, multiple parties, each holding an input, want to agree on a random permutation of their inputs while keeping the permutation secret. This problem is important as a primitive in many privacy-preserving applications such as anonymous communication, location-based services, and electronic voting. Known techniques for solving this problem suffer from poor scalability, load-balancing issues, trusted party assumptions, and/or weak security guarantees. In this paper, we propose an unconditionally-secure protocol for multi-party shuffling that scales well with the number of parties and is load-balanced. In particular, we require each party to send only a polylogarithmic number of bits and perform a polylogarithmic number of operations while incurring only a logarithmic round complexity. We show security under universal composability against up to about n/3 fully-malicious parties. We also provide simulation results showing that our protocol im-proves significantly over previous work. For example, for one million parties, when compared to the state of the art, our protocol reduces the communication and computation costs by at least three orders of magnitude and slightly decreases the number of communication rounds. 1
Data-oblivious algorithms are a key component of many secure computation protocols. In this work, we show that advances in secure multiparty shuffling algorithms can be used to increase the efficiency of several key cryptographic tools. The key observation is that many secure computation protocols rely heavily on secure shuffles. The best data-oblivious shuffling algorithms require O(n log n), operations, but in the two-party or multiparty setting, secure shuffling can be achieved with only O(n) communication. Leveraging the efficiency of secure multiparty shuffling, we give novel, information-theoretic algorithms that improve the efficiency of securely sorting sparse lists, secure stable compaction, and securely merging two sorted lists. Securely sorting private lists is a key component of many larger secure computation protocols. The best data-oblivious sorting algorithms for sorting a list of n elements require O(n log n) comparisons. Using black-box access to a linear-communication secure shuffle, we give a secure algorithm for sorting a list of length n with t ≪ n nonzero elements with communication O(t log² n + n), which beats the best oblivious algorithms when the number of nonzero elements, t, satisfies t < n/log² n. Secure compaction is the problem of removing dummy elements from a list, and is essentially equivalent to sorting on 1-bit keys. The best oblivious compaction algorithms run in O(n)-time, but they are unstable, i.e., the order of the remaining elements is not preserved. Using black-box access to a linear-communication secure shuffle, we give an information-theoretic stable compaction algorithm with only O(n) communication. Our main result is a novel secure merge protocol. The best previous algorithms for securely merging two sorted lists into a sorted whole required O(n log n) secure operations. Using black-box access to an O(n)-communication secure shuffle, we give the first multi-party secure merge algorithm that requires only O(n log log n) communication. Our algorithm takes as input n secret-shared values, and outputs a secret-sharing of the sorted list. All our algorithms are generic, i.e., they can be implemented using generic secure computations techniques and make black-box access to a secure shuffle. Our techniques extend naturally to the multiparty situation (with a constant number of parties) as well as to handle malicious adversaries without changing the asymptotic efficiency. These algorithm have applications to securely computing database joins and order statistics on private data as well as multiparty Oblivious RAM protocols.
We revisit shuffle protocols for Shamir secret sharing. Existing constructions either produce non-uniform shuffles or incur high communication and round complexity, sometimes exponential in the number of parties. We propose two new shuffle protocols that achieve uniform shuffling with communication complexity O ( k + l log k n 2 m log m ) for an m × l matrix shared among n parties, where k ≤ m is a tunable parameter. The first protocol is concretely efficient, while the second achieves the best-known O ( n m l ) online communication and O ( n ) rounds. Experiments show significant improvements in online efficiency and total cost over prior work. Our key technical ingredient is a novel permutation sharing technique that represents permutations via smaller permutation matrices, making their application significantly more efficient. The first protocol applies independent secret permutations sequentially, while the second builds on shuffle correlation to achieve optimal online complexity. We further extend shuffle correlation to support guaranteed output delivery with linear online communication, yielding SLIDE (shuffle Shamir secret shares uniformly with linear online communication and guaranteed output delivery), the first protocol achieving both O ( n m l ) online communication and guaranteed output delivery. Our constructions rely only on basic Shamir secret sharing over any field F with | F | > n . As shuffling is a fundamental primitive for multiparty computation tasks such as sorting and oblivious data structures, our results enable more efficient and scalable secure computation in practice.
We are interested in secure computation protocols in settings where the number of parties is huge and their data even larger. Assuming the existence of a single-use broadcast channel (per player), we demonstrate statistically secure computation protocols for computing (multiple) arbitrary dynamic RAM programs over parties ’ inputs, handling (1/3−) fraction static corrup-tions, while preserving up to polylogarithmic factors the computation and memory complexities of the RAM program. Additionally, our protocol is load balanced and has polylogarithmic communication locality.
Secure multi-party computation (MPC) is one of the most important primitives in cryptography. Several directions to construct and improve MPC protocols have been studied over the past decades. The majority of existing MPC protocols rely on assumptions such as every party communicates with every other party or every party needs to know every other party and the computation algorithm well in advance. Such assumptions can be difficult to achieve in modern large scale networks. This thesis explores two distinct lines of work leading to new practical models in response to these scenarios.First, we examine communication locality, the total number of other parties that each party communicates with in the protocol, as a new measure for an MPC protocol. Although progress has been made, the question of achieving low communication locality and round complexity at the same time for adaptive adversaries corrupting t l n/2 parties remains open. We show that by assuming a public-key infrastructure (PKI) and a symmetric-key infrastructure (SKI) the above question can be answered affirmatively, under standard assumptions. In particular, we describe a protocol with polylogarithmic communication locality and round complexity which tolerates up to t l n/2 adaptive corruptions. Our results are based on a new model of hidden random graphs obtained from the SKI, and using them to emulate a complete network in polylogarithmic rounds and polylogarithmic locality.We then examine multi-key fully homomorphic encryption (MFHE) schemes, which allow computation on data encrypted under different public keys chosen independently of each other. One of the main problems left in MFHE has been on how to deal with malicious users without trusted setup assumptions. We show how this can be done through circuit privacy, which guarantees that even if both ciphertexts and public keys are not well-formed, no information is revealed regarding the computation, other than what follows from the output on some well-formed inputs. Generalizing the result for circuit-private FHE, we provide a framework for adding circuit privacy to existing MFHE schemes.Finally, we incorporate the circuit privacy in a variant of server-assisted MPC, called on-the-fly MPC, where a server or a “cloud” performs an arbitrary dynamically chosen computation on a subset of data uploaded by multiple clients and encrypted under different keys on-the-fly. Circuit privacy allows the server to keep the algorithm used in the computation private even from a malicious adversary corrupting any number of clients. In particular, we construct a three-round on-the-fly MPC protocol with circuit privacy against malicious clients without the trusted setup.
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.