Secure Multiparty Computation Goes Live

Bogetoft, Peter; Christensen, Dan Lund; Damgård, Ivan; Geisler, Martin; Jakobsen, Thomas P.; Krøigaard, Mikkel; Nielsen, Janus Dam; Nielsen, Jesper Buus; Nielsen, Kurt; Pagter, Jakob; Schwartzbach, Michael I.; Toft, Tomas

doi:10.1007/978-3-642-03549-4_20

Cited by 415 publications

(267 citation statements)

References 22 publications

Supporting

Mentioning

264

Contrasting

Unclassified

Order By: Relevance

“…Until recently all work on secure multi-party computation has been essentially of a theoretical nature, focusing on feasibility results. However in the last few years a number of practical implementations have appeared [3,5,6,22,24].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Secure Two-Party Computation Is Practical

Pinkas

Schneider

Smart

et al. 2009

Advances in Cryptology – ASIACRYPT 2009

337

348

View full text Add to dashboard Cite

Abstract. Secure multi-party computation has been considered by the cryptographic community for a number of years. Until recently it has been a purely theoretical area, with few implementations with which to test various ideas. This has led to a number of optimisations being proposed which are quite restricted in their application. In this paper we describe an implementation of the two-party case, using Yao's garbled circuits, and present various algorithmic protocol improvements. These optimisations are analysed both theoretically and empirically, using experiments of various adversarial situations. Our experimental data is provided for reasonably large circuits, including one which performs an AES encryption, a problem which we discuss in the context of various possible applications.

show abstract

Section: Introductionmentioning

confidence: 99%

“…This approach has been used to great effect in the SIMAP project [6], which has resulted in a "real-life" application of secure multi-party computation to the Danish sugar beet industry [5].…”

Section: Introductionmentioning

confidence: 99%

Secure Two-Party Computation Is Practical

Pinkas

Schneider

Smart

et al. 2009

Advances in Cryptology – ASIACRYPT 2009

337

348

View full text Add to dashboard Cite

show abstract

“…-Honest-majority MPC. Recent large-scale practical uses of MPC [10,9] employed three servers and assumed that at most one of these servers is corrupted by a semi-honest adversary. Protocols in the correlated randomness model can be translated into protocols in this 3-server model by simply letting one server generate the correlated randomness for the other two.…”

Section: Introductionmentioning

confidence: 99%

On the Power of Correlated Randomness in Secure Computation

Ishai

Kushilevitz

Meldgaard

et al. 2013

Theory of Cryptography

View full text Add to dashboard Cite

Abstract. We investigate the extent to which correlated secret randomness can help in secure computation with no honest majority. It is known that correlated randomness can be used to evaluate any circuit of size s with perfect security against semi-honest parties or statistical security against malicious parties, where the communication complexity grows linearly with s. This leaves open two natural questions: (1) Can the communication complexity be made independent of the circuit size? (2) Is it possible to obtain perfect security against malicious parties?We settle the above questions, obtaining both positive and negative results on unconditionally secure computation with correlated randomness. Concretely, we obtain the following results.Minimizing communication. Any multiparty functionality can be realized, with perfect security against semi-honest parties or statistical security against malicious parties, by a protocol in which the number of bits communicated by each party is linear in its input length. Our protocol uses an exponential number of correlated random bits. We give evidence that super-polynomial randomness complexity may be inherent.Perfect security against malicious parties. Any finite "senderreceiver" functionality, which takes inputs from a sender and a receiver and delivers an output only to the receiver, can be perfectly realized given correlated randomness. In contrast, perfect security is generally impossible for functionalities which deliver outputs to both parties. We also show useful functionalities (such as string equality) for which there are efficient perfectly secure protocols in the correlated randomness model.Perfect correctness in the plain model. We present a general approach for transforming perfectly secure protocols for sender-receiver On the Power of Correlated Randomness in Secure Computation 601 functionalities in the correlated randomness model into secure protocols in the plain model which offer perfect correctness against a malicious sender. This should be contrasted with the impossibility of perfectly sound zero-knowledge proofs.

show abstract

“…Each iteration involves several comparisons and a Gaussian elimination step, making it quite heavy for multiparty computation. For relatively small instances, passively secure linear programming is feasible [BD09,CdH10]; but actively secure MPC much less so when including preprocessing (as we discuss later). Fortunately, given a solution x to an LP, there is an easy way to prove that it is optimal using the optimal solution p of the so-called dual LP "maximise b · p such that A · p ≤ c, p ≤ 0".…”

Section: Secure and Verifiable Linear Programmingmentioning

confidence: 99%

Certificate Validation in Secure Computation and Its Use in Verifiable Linear Programming

Hoogh

Schoenmakers

Veeningen

2016

Progress in Cryptology – AFRICACRYPT 2016

View full text Add to dashboard Cite

Abstract. For many applications of secure multiparty computation it is natural to demand that the output of the protocol is verifiable. Verifiability should ensure that incorrect outputs are always rejected, even if all parties executing the secure computation collude. Since the inputs to a secure computation are private, and potentially the outputs are private as well, adding verifiability is in general hard and costly. In this paper we focus on privacy-preserving linear programming as a typical and practically relevant case for verifiable secure multiparty computation. We introduce certificate validation as an effective technique for achieving verifiable linear programming. Rather than verifying the computation proper, which involves many iterations of the simplex algorithm, we extend the output of the secure computation with a certificate. The certificate allows for efficient and direct validation of the correctness of the output. The overhead incurred by the computation of the certificate is marginal. For the validation of a certificate we design particularly efficient distributed-prover zero-knowledge proofs, fully exploiting the fact that we can use ElGamal encryption for this purpose, hence avoiding the use of more elaborate cryptosystems such as Paillier encryption. We also formulate appropriate security definitions for our approach, and prove security for our protocols in this model, paying special attention to ensuring properties such as input independence. By means of several experiments performed in a real multi-cloud-provider environment, we show that the overall performance for verifiable linear programming is very competitive, incurring minimal overhead compared to protocols providing no correctness guarantees at all.

show abstract

Secure Multiparty Computation Goes Live

Abstract: Abstract. In this note, we report on the first large-scale and practical application of multiparty computation, which took place in January 2008. We also report on the novel cryptographic protocols that were used.

Cited by 415 publications

References 22 publications

Secure Two-Party Computation Is Practical

Secure Two-Party Computation Is Practical

On the Power of Correlated Randomness in Secure Computation

Certificate Validation in Secure Computation and Its Use in Verifiable Linear Programming

Contact Info

Product

Resources

About