Adaptively Secure Multi-Party Computation with Dishonest Majority

We construct a four round secure multip arty computation (MPC) protocol in the plain model that achieves security against any dishonest majority. The security of our protocol relies only on the existence of four round oblivious transfer. This culminates the long line of research on constructing round-efficient MPC from minimal assumptions (at least w.r.t. black-box simulation).

Adaptively secure Multi-Party Computation MPC is an essential and fundamental notion in cryptography. In this work, we construct Universally Composable UC MPC protocols that are adaptively secure against all-but-one corruptions based on LWE. Our protocols have a constant number of rounds and communication complexity dependant only on the length of the inputs and outputs it is independent of the circuit size. Such protocols were only known assuming an honest majority. Protocols in the dishonest majority setting, such as the work of Ishai et al. CRYPTO 2008, require communication complexity proportional to the circuit size. In addition, constant-round adaptively secure protocols assuming dishonest majority are known to be impossible in the stand-alone setting with black-box proofs of security in the plain model. Here, we solve the problem in the UC setting using a set-up assumption which was shown necessary in order to achieve dishonest majority. The problem of constructing adaptively secure constant-round MPC protocols against arbitrary corruptions is considered a notorious hard problem. A recent line of works based on indistinguishability obfuscation construct such protocols with near-optimal number of rounds against arbitrary corruptions. However, based on standard assumptions, adaptively secure protocols secure against even just all-but-one corruptions with near-optimal number of rounds are not known. However, in this work we provide a three-round solution based only on LWE and NIZK secure against all-but-one corruptions. In addition, Asharov et al. EUROCRYPT 2012 and more recently Mukherjee and Wichs ePrint 2015 presented constant-round protocols based on LWE which are secure only in the presence of static adversaries. Assuming NIZK and LWE their static protocols run in two rounds where the latter one is only based on a common random string. Assuming adaptively secure UC NIZK, proposed by Groth et al. ACM 2012, and LWE as mentioned above our adaptive protocols run in three rounds. Our protocols are constructed based on a special type of cryptosystem we call equivocal FHE from LWE. We also build adaptively secure UC commitments and UC zero-knowledge proofs of knowledge from LWE. Moreover, in the decryption phase using an AMD code mechanism we avoid the use of ZK and achieve communication complexity that does not scale with the decryption circuit.

The last decade has seen an explosion in the number of new secure multi-party computation (MPC) protocols that enable collaborative computation on sensitive data. No single MPC protocol is optimal for all types of computation. As a result, researchers have created hybrid-protocol compilers that translate a program into a hybrid protocol that mixes different MPC protocols. Hybrid-protocol compilers crucially rely on accurate cost models, which are handwritten by the compilers' developers, to choose the correct schedule of protocols. In this paper, we propose CostCO, the first automatic MPC cost modeling framework. CostCO develops a novel API to interface with a variety of MPC protocols, and leverages domain-specific properties of MPC in order to enable efficient and automatic cost-model generation for a wide range of MPC protocols. CostCO employs a two-phase experiment design to efficiently synthesize cost models of the MPC protocol's runtime as well as its memory and network usage. We verify CostCO's modeling accuracy for several full circuits, characterize the engineering effort required to port existing MPC protocols, and demonstrate how hybrid-protocol compilers can leverage CostCO's cost models.

We study a model of fairness in secure computation in which an adversarial party that aborts on receiving output is forced to pay a mutually predefined monetary penalty. We then show how the Bitcoin network can be used to achieve the above notion of fairness in the two-party as well as the multiparty setting (with a dishonest majority). In particular, we propose new ideal functionalities and protocols for fair secure computation and fair lottery in this model.One of our main contributions is the definition of an ideal primitive, which we call \(\mathcal{F}_{\mathrm{CR}}^\star\) (CR stands for “claim-or-refund”), that formalizes and abstracts the exact properties we require from the Bitcoin network to achieve our goals. Naturally, this abstraction allows us to design fair protocols in a hybrid model in which parties have access to the \(\mathcal{F}_{\mathrm{CR}}^\star\) functionality, and is otherwise independent of the Bitcoin ecosystem. We also show an efficient realization of \(\mathcal{F}_{\mathrm{CR}}^\star\) that requires only two Bitcoin transactions to be made on the network.Our constructions also enjoy high efficiency. In a multiparty setting, our protocols only require a constant number of calls to \(\mathcal{F}_{\mathrm{CR}}^\star\) per party on top of a standard multiparty secure computation protocol. Our fair multiparty lottery protocol improves over previous solutions which required a quadratic number of Bitcoin transactions.KeywordsFair exchangeSecure computationBitcoin

The demanding need to perform privacy-preserving computations among multiple data owners has led to the prosperous development of secure multi-party computation (MPC) protocols. MPC offers protocols for parties to jointly compute a function over their inputs while keeping those inputs private. To date, MPC has been widely adopted in various real-world, privacy-sensitive sectors, such as healthcare and finance. Moreover, to ease the adoption of MPC, industrial and academic MPC compilers have been developed to automatically translate programs describing arbitrary MPC procedures into low-level MPC executables. Compiling high-level descriptions into high-efficiency MPC executables is challenging: the compilation often involves converting high-level languages into several intermediate representations (IR), e.g., arithmetic or boolean circuits, optimizing the computation/communication cost, and picking proper MPC protocols (and underlying virtual machines) for a particular task and threat model. Various optimizations and heuristics are employed during the compilation procedure to improve the efficiency of the generated MPC executables. Despite the prosperous adoption of MPC compilers by industrial vendors and academia, a principled and systematic understanding of the correctness of MPC compilers does not yet exist. To fill this critical gap, this paper introduces MT-MPC, a metamorphic testing (MT) framework specifically designed for MPC compilers to effectively uncover erroneous compilations. Our approach proposes three metamorphic relations (MRs) that are tailored for MPC programs to mutate high-level MPC programs (compiler inputs). We then examine if MPC compilers yield semantics-equivalent MPC executables regarding the original and mutated MPC programs by comparing their execution results. Real-world MPC compilers exhibit a high level of engineering quality. Nevertheless, we detected 4,772 inputs that can result in erroneous compilations in three popular MPC compilers available on the market. While the discovered error-triggering inputs do not cause the MPC compilers to crash directly, they can lead to the generation of incorrect MPC executables, jeopardizing the underlying dependability of the computation. With substantial manual effort and help from the MPC compiler developers, we uncovered thirteen bugs in these MPC compilers by debugging them using the error-triggering inputs. Our proposed testing frameworks and findings can be used to guide developers in their efforts to improve MPC compilers.

Secure multiparty computation protocol based on homomorphic encryption and its application in blockchain

Secure multi-party computation (MPC) is a fundamental problem in secure distributed computing. An MPC protocol allows a set of $n$ mutually distrusting parties to carry out any joint computation of their private inputs, without disclosing any additional information about their inputs. MPC with information-theoretic security provides the strongest security guarantees and remains secure even against computationally unbounded adversaries. Perfectly-secure MPC protocols is a class of information-theoretically secure MPC protocols, which provides all the security guarantees in an error-free fashion. The focus of this work is perfectly-secure MPC. Known protocols are designed assuming either a synchronous or asynchronous communication network. It is well known that perfectly-secure synchronous MPC protocol is possible as long as adversary can corrupt any $t_s < n/3$ parties. On the other hand, perfectly-secure asynchronous MPC protocol can tolerate up to $t_a < n/4$ corrupt parties. A natural question is does there exist a single MPC protocol for the setting where the parties are not aware of the exact network type and which can tolerate up to $t_s < n/3$ corruptions in a synchronous network and up to $t_a < n/4$ corruptions in an asynchronous network. We design such a best-of-both-worlds perfectly-secure MPC protocol, provided $3t_s + t_a < n$ holds. For designing our protocol, we design two important building blocks, which are of independent interest. The first building block is a best-of-both-worlds Byzantine agreement (BA) protocol tolerating $t < n/3$ corruptions and which remains secure, both in a synchronous as well as asynchronous network. The second building block is a polynomial-based best-of-both-worlds verifiable secret-sharing (VSS) protocol, which can tolerate up to $t_s$ and $t_a$ corruptions in a synchronous and in an asynchronous network respectively.

With the rise of practical Secure Multi-party Computation (MPC) protocols, compilers have been developed that create Boolean or Arithmetic circuits for MPC from functionality descriptions in a high-level language. Previous compilers focused on the creation of size-minimal circuits. However, many MPC protocols, such as GMW and SPDZ, have a round complexity that is dependent on the circuit’s depth. When deploying these protocols in real world network settings, with network latencies in the range of tens or hundreds of milliseconds, the round complexity quickly becomes a significant performance bottleneck.

In the setting of secure multiparty computation, a set of parties wish to compute a joint function of their private inputs. The computation should preserve security properties such as privacy, correctness, independence of inputs, fairness and guaranteed output delivery. In the case of no honest majority, fairness and guaranteed output delivery cannot always be obtained. Thus, protocols for secure multiparty computation are typically of two disparate types: protocols that assume an honest majority (and achieve all properties including fairness and guaranteed output delivery), and protocols that do not assume an honest majority (and achieve all properties except for fairness and guaranteed output delivery). In addition, in the two-party case, fairness and guaranteed output delivery are equivalent. As a result, the properties of fairness (which means that if corrupted parties receive output then so do the honest parties) and guaranteed output delivery (which means that corrupted parties cannot prevent the honest parties from receiving output in any case) have typically been considered to be the same.

In this work, we consider executions of smart contracts for implementing secure multi-party computation (MPC) protocols on forking blockchains (e.g., Ethereum), and we study security and delay issues due to forks. In this setting, the classical double-spending problem tells us that messages of the MPC protocol should be confirmed on-chain before playing the next ones, thus slowing down the entire execution.Our contributions are twofold: For the concrete case of fairly tossing multiple coins with penalties, we notice that the lottery protocol of Andrychowicz et al. (S&P ’14) becomes insecure if players do not wait for the confirmations of several transactions. In addition, we present a smart contract that instead retains security even when all honest players immediately answer to transactions appearing on-chain. We analyze the performance using Ethereum as testbed. We design a compiler that takes any “digital and universally composable” MPC protocol (with or without honest majority), and transforms it into another one (for the same task and same setup) which maintains security even if all messages are played on-chain without delays. The special requirements on the starting protocol mean that messages consist only of bits (e.g., no hardware token is sent) and security holds also in the presence of other protocols. We further show that our compiler satisfies fairness with penalties as long as honest players only wait for confirmations once. By reducing the number of confirmations, our protocols can be significantly faster than natural constructions.KeywordsMPCBlockchainFinalityForksSmart contracts

The notion of covert computation, an enhanced form of secure multiparty computation, allows parties to jointly compute a function, while ensuring that participating parties cannot distinguish their counterparties from a random noise generator, until the end of the protocol, when the output of the function is revealed, if favorable to all parties. Previous works on covert computation achieved super-constant round protocols for general functionalities [5, 16], with efficiency at least linear in the size of the circuit representation of the computed function. Indeed, [9] showed that constant-round covert computation of any non-trivial functionality with black-box simulation is impossible in the plain model. In this work we construct the first practical constant-round covert protocol for a non-trivial functionality, namely the set-intersection functionality, in the Random Oracle Model. Our construction demonstrates the usefulness of covert subprotocols as building blocks in constructing larger protocols: We show how to compile a concurrently covert protocol for a single-input functionality, e.g. string equality, into an efficient secure and covert protocol for a corresponding multi-input functionality, e.g. set intersection. Our main contributions are summarized as follows:We upgrade the notion of covert computation of [5] to concurrent covert computation.We provide a general compiler that converts concurrent covert protocols for single-input functionalities to concurrent covert protocols for corresponding multi-input counterparts of these functionalities, at linear cost, in the Random Oracle Model.To demonstrate the usefulness of our compiler, we construct a concurrently covert string equality protocol and then apply our compiler to achieve a two-message concurrent covert protocol for Set Intersection SI with a linear cost in the Random Oracle Model.

Demand for distributed computational infrastructure is growing in order to offer low latency connections to end users. The fragmenting infrastructure complicates the resource allocation process. As the number of infrastructure providers grows, points of presence are resource constrained compared to the cloud, they have diverse availability profiles, and diverse connectivity properties. Existing resource allocation approaches require providers share intimate details about their infrastructure to support the placement process, or rely on third party aggregators. Such solutions introduce strong assumptions of trust and collaboration. In this work we present Angler, the first system to allocate resources from dark pools, meaning the capacity and requests of the distributed pool of resources are unknown. Angler leverages cryptographic protocols for secure function evaluation, namely the WRK secure multiparty computation (MPC) protocol [76]. While MPC protocols can have large overheads compared to plaintext function evaluation, an end-to-end approach to the system design subverts the expensive overheads. Specifically, Angler combines a tuned implementation of a maliciously secure MPC protocol, a tailored distributed hash table, and a systematic effort to make the best allocation decision within a response time envelope. Angler is only 2x slower than resource allocation with no privacy when arbitrating among 8 providers, taking less than a second.

Secure multi-party computations for privacy-preserving machine learning

Recent developments in the automatic transformation of protocols into Secure Multiparty Computation (SMC) interactions, and the selection of appropriate schemes for their implementation have improved usabililty of SMC. Poor performance along with data leakage or errors caused by coding mistakes and complexity had hindered SMC usability. Previous practice involved integrating the SMC code into the application being designed, and this tight integration meant the code was not reusable without modification. The progress that has been made to date towards the selection of different schemes focuses solely on the two-party paradigm in a static set-up, and does not consider changing contexts. Contexts, for secure multiparty computation, include the number of participants, link latency, trust and security requirements such as broadcast, dishonest majority etc. Variable Interpretation is a concept we propose whereby specific domain constructs, such as multiparty computation descriptions, are explicitly removed from the application code and expressed in SMC domain representation. This mirrors current practice in presenting a language or API to hide SMC complexity, but extends it by allowing the interpretation of the SMC to be adapted to the context. It also decouples SMC from human co-ordination by introducing a rule-based dynamic negotiation of protocols. Experiments were carried out to validate the method, running a multiparty computation on a variable interpreter for SMC using different protocols in different contexts.

Secure multi-party computation (SMC) is a cryptographic protocol that allows participants to compute the desired output without revealing their inputs. A variety of results related to increasing the efficiency of SMC protocol have been reported, and thus, SMC can be used in various applications. With the SMC protocol in smart grids, it becomes possible to obtain information for load balancing and various statistics, without revealing sensitive user information. To prevent malicious users from tampering with input values, SMC requires cheater detection. Several studies have been conducted on SMC with cheater detection, but none of these has been able to guarantee the fairness of the protocol. In such cases, only a malicious user can obtain a correct output prior to detection. This can be a critical problem if the result of the computation is real-time information of considerable economic value. In this paper, we propose a fair and secure multi-party computation protocol, which detects malicious parties participating in the protocol before computing the final output and prevents them from obtaining it. The security of our protocol is proven in the universal composability framework. Furthermore, we develop an enhanced version of the protocol that is more efficient when computing an average after detecting cheaters. We apply the proposed protocols to a smart grid as an application and analyze their efficiency in terms of computational cost.