Mathematical Problems of Computer Science

Secure Multiparty Computations for Collaboration between Competing Service Providers

Davit H. Danoyan

Published Jan 1, 2016• 0 citations

Abstract

We introduce a platform for secure computations and describe the platform workflow. We detail the Golreich-Micalli-Widgerson protocol employed for secure multiparty computation in our platform with optimization techniques applied to it. Being based on white-box cryptography, the underlying oblivious transfer protocol avoids the use of expensive public key operations and provides good overhead compared to similar systems. Also we point out some useful application scenarios and provide a real world application design based on our platform.

Related papers

Optimization Techniques for Generic Secure Two-party Computation Platform

Tigran V. Sokhakyan

In this article we present an implementation of general purpose secure twoparty computation framework offering security against semi-honest threat model. Proposed framework implements Yao’s garbled circuits protocol and incorporates novel oblivious transfer protocol based on white-box cryptography methods for the first time to avoid computationally expensive public key operations. Also experimental results illustrating the efficiency of our framework compared with previous implementations are provided.

Mathematical Problems of Computer ScienceMar 15, 20160 citations

Secure Computation in Heterogeneous Environments: How to Bring Multiparty Computation Closer to Practice?

Raykova, Mariana Petrova

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.

Jan 1, 20124 citations

Experimental secure multiparty computation from quantum oblivious transfer with bit commitment

Kaiyi Zhang, An-Jing Huang, Kun Tu +5 more

Secure multiparty computation enables collaborative computations across multiple users while preserving individual privacy, which has a wide range of applications in finance, machine learning and healthcare. Secure multiparty computation can be realized using oblivious transfer as a primitive function. In this paper, we present an experimental implementation of a quantum-secure quantum oblivious transfer (QOT) protocol using an adapted quantum key distribution system combined with a bit commitment scheme, surpassing previous approaches only secure in the noisy storage model. We demonstrate the first practical application of the QOT protocol by solving the private set intersection, a prime example of secure multiparty computation, where two parties aim to find common elements in their datasets without revealing any other information. In our experiments, two banks can identify common suspicious accounts without disclosing any other data. This not only proves the experimental functionality of QOT, but also showcases its real-world commercial applications.

arXiv:2411.04558npj Quantum InformationMar 14, 20260 citations

Round-Optimal Secure Multiparty Computation from Minimal Assumptions

Akshayaram Srinivasan

Secure Multiparty Computation (MPC) allows a set of parties, each having its own private data, to compute a function of their joint data such that the parties only learn the output of this function and everything else about their data is hidden. MPC is a fundamental cryptographic abstraction that captures many other natural cryptographic primitives as special cases. It also has a wide range of practical applications such as conducting secure electronic auctions, delegating sensitive computation to untrusted cloud service providers, secure computation on genomic data and training machine learning models on private data.A long-standing open problem in this area is to construct MPC protocols that have {\\it optimal} (two-round) round complexity under the {\\it weakest} possible cryptographic hardness assumptions.We {\\it completely resolve} this problem by showing lower bounds and matching upper bounds on the hardness assumptions required for constructing round-optimal MPC. Specifically, we obtain the following results.\\begin{itemize}\\item \\textbf{Black-Box Separation.} We show that there exists no construction of two-round semi-honest MPC protocol for general functions that makes black-box use of a two-round oblivious transfer. As a corollary, a similar separation holds when starting with any 2-party functionality other than oblivious transfer. \\item \\textbf{Non-Black-Box Construction.} We show that the above negative result can be bypassed by making non-black-box use of a two-round oblivious transfer. Specifically, starting from a semi-honest (resp. malicious) secure two-round oblivious transfer protocol, we construct a two-round MPC protocol against semi-honest (resp. malicious) adversaries. \\end{itemize}Since any two-round MPC protocol for general functionalities implies a two-round oblivious transfer as a special case, the above two results show that non-black-box use of oblivious transfer is {\\it necessary and sufficient} to construct round-optimal MPC protocols.

Jan 1, 20200 citations

More efficient oblivious transfer and extensions for faster secure computation

Gilad Asharov, Yehuda Lindell, Thomas H. Schneider +1 more

Protocols for secure computation enable parties to compute a joint function on their private inputs without revealing anything but the result. A foundation for secure computation is oblivious transfer (OT), which traditionally requires expensive public key cryptography. A more efficient way to perform many OTs is to extend a small number of base OTs using OT extensions based on symmetric cryptography.

ACM SIGSAC Conference on Computer and Communications Security (CCS)Jan 1, 2013365 citations

Generation and Distribution of Quantum Oblivious Keys for Secure Multiparty Computation

Mariano Lemus, Mariana F. Ramos, Preeti Yadav +6 more

The oblivious transfer primitive is sufficient to implement secure multiparty computation. However, secure multiparty computation based on public-key cryptography is limited by the security and efficiency of the oblivious transfer implementation. We present a method to generate and distribute oblivious keys by exchanging qubits and by performing commitments using classical hash functions. With the presented hybrid approach of quantum and classical, we obtain a practical and high-speed oblivious transfer protocol. We analyse the security and efficiency features of the technique and conclude that it presents advantages in both areas when compared to public-key based techniques.

arXiv:1909.11701Applied SciencesJun 12, 202026 citations