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IEEE Transactions on Information Forensics and Security

Load-Balanced Server-Aided MPC in Heterogeneous Computing

Yibiao Lu, Bingsheng Zhang, Kui Ren

Published Nov 8, 2024• 0 citations
Publisher

Abstract

Most existing MPC protocols consider the homogeneous setting, where all the MPC players are assumed to have identical communication and computation resources. In practice, the player with the least resources often becomes the bottleneck of the entire MPC protocol execution. In this work, we initiate the study of so-calledload-balanced MPCin heterogeneous computing. A load-balanced MPC protocol can adjust the workload of each player accordingly to maximize the overall resource utilization. In particular, we propose new notions calledcomposite circuitandcomposite garbling scheme, and construct two efficient server-aided protocols with malicious security and semi-honest security, respectively. Our maliciously secure protocol is over$400\times $faster than the authenticated garbling protocol (CCS ’17) and up to$4.3\times $faster than the state-of-the-art server-aided MPC protocol of Lu et al. (TDSC ’23); our semi-honest protocol is up to$173\times $faster than the optimized BMR protocol (CCS ’16) and is up to$3.8\times $faster than the protocol of Lu et al.

DOI
10.1109/tifs.2024.3494547

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Most existing MPC protocols consider the homogeneous setting, where all the MPC players are assumed to have identical communication and computation resources. In practice, the player with the least resources often becomes the bottleneck of the entire MPC protocol execution. In this work, we initiate the study of so-calledload-balanced MPCin heterogeneous computing. A load-balanced MPC protocol can adjust the workload of each player accordingly to maximize the overall resource utilization. In particular, we propose new notions calledcomposite circuitandcomposite garbling scheme, and construct two efficient server-aided protocols with malicious security and semi-honest security, respectively. Our maliciously secure protocol is over400×400\times 400×faster than the authenticated garbling protocol (CCS ’17) and up to4.3×4.3\times 4.3×faster than the state-of-the-art server-aided MPC protocol of Lu et al. (TDSC ’23); our semi-honest protocol is up to173×173\times 173×faster than the optimized BMR protocol (CCS ’16) and is up to3.8×3.8\times 3.8×faster than the protocol of Lu et al.
Secure multi-party computation (MPC) provides provable security guarantees for many privacy critical applications. The semi-honest MPC protocols are secure against semi-honest adversaries who can only observe the protocol execution, while the maliciously secure MPC protocols are secure against malicious adversaries who can deviate from the protocol description arbitrarily. Many security sensitive applications tend to use semi-honest MPC protocols because malicious security comes with huge communication and/or computation costs. In this work, we show how to efficiently transform generic semi-honest two-party protocols into maliciously secure multi-party protocol in the server-aided setting. We further propose an optimized constant-round server-aided MPC protocol. The proposed protocols are secure when all but one parties are maliciously corrupted, while the remaining party and the server are corrupted by semi-honest and non-colluding adversaries. We implement and evaluate our constant-round protocol. For the 2-party case, our protocol is only 1.11× slower than thesemi-honestYao's Garbled Circuits protocol, and it is 9.16× faster than the maliciously secure authenticated garbling protocol and 4.96× faster than the state-of-the-art maliciously secure server-aided protocol of Wuet al.For the 8-party case, our protocol is 103.29× faster than the authenticated garbling protocol and 17.03× faster than the protocol of Wuet al.
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 servers, and accept the same corruption threshold. In this paper, we challenge this assumption and introduce a new paradigm for server-aided MPC, where each client can choose their own set of servers and their own threshold of corrupted servers. In this new model, the privacy of each client is guaranteed as long as their own threshold is satisfied, regardless of the other servers/clients. We call this paradigm per-party private server-aided MPC to highlight both a security and efficiency guarantee: (1) per-party privacy, which means that each party gets their own privacy guarantees that depend on their own choice of the servers; (2) per-party complexity, which means that each party only needs to communicate with their chosen servers. Our primary contribution is a new theoretical framework for server-aided MPC. We provide two protocols to show feasibility, but leave it as a future work to investigate protocols that focus on concrete efficiency.
Secure Multi-Party Computation (MPC) protocols allow a group of mutually distrusting users to compute a function jointly on their inputs without revealing any information beyond the output. For many years, implementations of MPC protocols have targeted security against semi-honest adversaries, i.e., attackers are assumed to execute the protocol honestly but try to learn private information after the fact. Protocols secure against stronger and more realistic malicious adversaries, who could behave arbitrarily during the protocol execution, were known to exist but were much less efficient. This thesis introduces a new paradigm to construct extremely efficient MPC protocols with malicious security. In particular, this thesis consists of three major contributions. 1. We introduce the authenticated garbling framework, and present an efficient concrete instantiation of the protocol. The resulting protocol partially closes the gap between semi-honest and malicious MPC protocols asymptotically; the implementation of the protocol represents the state-of-the-art system for malicious two-party computation. 2. We discuss how to apply authenticated garbling to the multi-party setting, where all-but-one parties can be corrupted by the adversary. The resulting protocol improves upon the best previous constant-round protocol by orders of magnitude. We also present a system that, for the first time, enables MPC executions among hundreds of parties, distributed globally. 3. We present a series of optimizations to two-party authenticated garbling by interpreting authenticated garbling in a new way. The improved malicious protocol has essentially the same concrete efficiency as the best semi-honest protocol in the preprocessing model. 4. We develop these protocols in EMP-toolkit, a practical and efficient MPC tool that can be used to build new protocols and to develop applications using our existing protocols.
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.
Many services that people use daily require computation that depends on the private data of multiple parties. While the utility of the final result of such interactions outweighs the privacy concerns related to output release, the inputs for such computations are much more sensitive and need to be protected. Secure multiparty computation (MPC) considers the question of constructing computation protocols that reveal nothing more about their inputs than what is inherently leaked by the output. There have been strong theoretical results that demonstrate that every functionality can be computed securely. However, these protocols remain unused in practical solutions since they introduce efficiency overhead prohibitive for most applications. Generic multiparty computation techniques address homogeneous setups with respect to the resources available to the participants and the adversarial model. On the other hand, realistic scenarios present a wide diversity of heterogeneous environments where different participants have different available resources and different incentives to misbehave and collude. In this thesis we introduce techniques for multiparty computation that focus on heterogeneous settings. We present solutions tailored to address different types of asymmetric constraints and improve the efficiency of existing approaches in these scenarios. We tackle the question from three main directions: New Computational Models for MPC - We explore different computational models that enable us to overcome inherent inefficiencies of generic MPC solutions using circuit representation for the evaluated functionality. First, we show how we can use random access machines to construct MPC protocols that add only polylogarithmic overhead to the running time of the insecure version of the underlying functionality. This allows to achieve MPC constructions with computational complexity sublinear in the size for their inputs, which is very important for computations that use large databases. We also consider multivariate polynomials which yield more succinct representations for the functionalities they implement than circuits, and at the same time a large collection of problems are naturally and efficiently expressed as multivariate polynomials. We construct an MPC protocol for multivariate polynomials, which improves the communication complexity of corresponding circuit solutions, and provides currently the most efficient solution for multiparty set intersection in the fully malicious case. Outsourcing Computation - The goal in this setting is to utilize the resources of a single powerful service provider for the work that computationally weak clients need to perform on their data. We present a new paradigm for constructing verifiable computation (VC) schemes, which enables a computationally limited client to verify efficiently the result of a large computation. Our construction is based on attribute-based encryption and avoids expensive primitives such as fully homomorphic encryption andprobabilistically checkable proofs underlying existing VC schemes. Additionally our solution enjoys two new useful properties: public delegation and verification. We further introduce the model of server-aided computation where we utilize the computational power of an outsourcing party to assist the execution and improve the efficiency of MPC protocols. For this purpose we define a new adversarial model of non-collusion, which provides room for more efficient constructions that rely almost completely only on symmetric key operations, and at the same time captures realistic settings for adversarial behavior. In this model we propose protocols for generic secure computation that offload the work of most of the parties to the computation server. We also construct a specialized server-aided two party set intersection protocol that achieves better efficiencies for the two participants than existing solutions. Outsourcing in many cases concerns only data storage and while outsourcing the data of a single party is useful, providing a way for data sharing among different clients of the service is the more interesting and useful setup. However, this scenario brings new challenges for access control since the access control rules and data accesses become private data for the clients with respect to the service provide. We propose an approach that offers trade-offs between the privacy provided for the clients and the communication overhead incurred for each data access. Efficient Private Search in Practice - We consider the question of private search from a different perspective compared to traditional settings for MPC. We start with strict efficiency requirements motivated by speeds of available hardware and what is considered acceptable overhead from practical point of view. Then we adopt relaxed definitions of privacy, which still provide meaningful security guarantees while allowing us to meet the efficiency requirements. In this setting we design a security architecture and implement a system for data sharing based on encrypted search, which achieves only 30% overhead compared to non-secure solutions on realistic workloads.
Secure multiparty computation (MPC) enables a set of parties to securely carry out a joint computation of their private inputs without revealing anything but the output. Protocols for semi-honest adversaries guarantee security as long as the corrupted parties run the specified protocol and ensure that nothing is leaked in the transcript. In contrast, protocols for malicious adversaries guarantee security in the presence of arbitrary adversaries who can run any attack strategy. Security for malicious adversaries is typically what is needed in practice (and is always preferred), but comes at a significant cost. In this paper, we present the first protocol for a two-thirds honest majority that achieves security in the presence of malicious adversariesat essentially the exact same cost as the best known protocols for semi-honest adversaries. Our construction is not a general transformation and thus it is possible that better semi-honest protocols will be constructed which do not support our transformation. Nevertheless, for the current state-of-the-art for many parties (based on Shamir sharing), our protocol invokes the best semi-honest multiplication protocol exactly once per multiplication gate (plus some additional local computation that is negligible to the overall cost). Concretely, the best version of our protocol requires each party to send on average of just 2 2/3 elements per multiplication gate (when the number of multiplication gates is at least the number of parties). This is four times faster than the previous-best protocol of Barak et al. (ACM CCS 2018) for small fields, and twice as fast as the previous-best protocol of Chida et al. (CRYPTO 2018) for large fields.