Multiparty Computation for Dishonest Majority: From Passive to Active Security at Low Cost

Damgård, Ivan; Orlandi, Claudio

doi:10.1007/978-3-642-14623-7_30

Cited by 48 publications

(24 citation statements)

References 23 publications

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“…Concretely, each party performs O(n 2 ) multiplications modulo p to evaluate a secure multiplication. This improves on the previous protocol of Damgård and Orlandi (DO) [DO10] where a Pedersen commitment was published for every shared value. Getting rid of the commitments we improve on efficiency (a factor of Ω(κ), where κ is the security parameter) and security (information theoretic against computational).…”

Section: Introductionmentioning

confidence: 57%

Semi-homomorphic Encryption and Multiparty Computation

Bendlin

Damgård

Orlandi

et al. 2011

Lecture Notes in Computer Science

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267

201

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Abstract. An additively-homomorphic encryption scheme enables us to compute linear functions of an encrypted input by manipulating only the ciphertexts. We define the relaxed notion of a semihomomorphic encryption scheme, where the plaintext can be recovered as long as the computed function does not increase the size of the input "too much". We show that a number of existing cryptosystems are captured by our relaxed notion. In particular, we give examples of semi-homomorphic encryption schemes based on lattices, subset sum and factoring. We then demonstrate how semi-homomorphic encryption schemes allow us to construct an efficient multiparty computation protocol for arithmetic circuits, UC-secure against a dishonest majority. The protocol consists of a preprocessing phase and an online phase. Neither the inputs nor the function to be computed have to be known during preprocessing. Moreover, the online phase is extremely efficient as it requires no cryptographic operations: the parties only need to exchange additive shares and verify information theoretic MACs. Our contribution is therefore twofold: from a theoretical point of view, we can base multiparty computation on a variety of different assumptions, while on the practical side we offer a protocol with better efficiency than any previous solution.

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Section: Introductionmentioning

confidence: 57%

Semi-homomorphic Encryption and Multiparty Computation

Bendlin

Damgård

Orlandi

et al. 2011

Lecture Notes in Computer Science

Self Cite

267

201

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show abstract

“…In the most general case, secure exact, approximate and single-character wildcards pattern matching is an instance of general secure two-party computation techniques (for instance, [24,25,26,27]). All of these schemes have bandwidth and computational complexity at best linear in the circuit size.…”

Section: Comparison To Previous Workmentioning

confidence: 99%

5PM: Secure Pattern Matching

Baron

Defrawy

Minkovich

et al. 2012

Lecture Notes in Computer Science

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Abstract. In this paper we consider the problem of secure pattern matching that allows singlecharacter wildcards and substring matching in the malicious (stand-alone) setting. Our protocol, called 5PM, is executed between two parties: Server, holding a text of length n, and Client, holding a pattern of length m to be matched against the text, where our notion of matching is more general and includes non-binary alphabets, non-binary Hamming distance and non-binary substring matching.5PM is the first secure expressive pattern matching protocol designed to optimize round complexity by carefully specifying the entire protocol round by round. In the malicious model, 5PM requires O((m + n)k 2 ) bandwidth and O(m + n) encryptions, where m is the pattern length and n is the text length. Further, 5PM can hide pattern size with no asymptotic additional costs in either computation or bandwidth. Finally, 5PM requires only two rounds of communication in the honest-but-curious model and eight rounds in the malicious model. Our techniques reduce pattern matching and generalized Hamming distance problems to a novel linear algebra formulation that allows for generic solutions based on any additively homomorphic encryption. We believe our efficient algebraic techniques are of independent interest.

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“…Efficiency improvements were also designed for multi-party computation, [44], by optimising AES encryption; their ideas can be applied when implementing the encrypion in our protocols. A new multi-party protocol to securely evaluate reactive arithmetic circuits, offering security against an active adversary in the universally composable security framework, was proposed by [45]; the protocol is based on a design of an efficient 'cut-and-choose' technique. Techniques reducing the size of garbled tables, thus improving computation and communication complexity, were proposed in [46]; the design of the gates rely on a 'free-XOR' technique.…”

Section: Efficiency Discussionmentioning

confidence: 99%

Oblivious and fair server-aided two-party computation

Herzberg

Shulman

2013

Information Security Technical Report

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We show efficient, practical (server-aided) secure two-party computation protocols ensuring privacy, correctness and fairness in the presence of malicious (Byzantine) faults. Our requirements from the server are modest. To ensure privacy and correctness, we only assume trusted execution service, executing an initialization program provided by both parties. To further ensure fairness, we further assume a trusted-decryption service, providing decryption service using known public key.Both of these trusted services are feasible in practice, and may be useful for additional tasks; both can also be distributed, with linear overhead, for redundancy. Formally, we model them as ideal functionalities, allowing proof of security using the hybrid model. Our fairness-ensuring protocol is optimistic, i.e., the decryption service is invoked only in case of faults. We believe that the protocols are sufficiently efficient, to allow deployment, in particular for financial applications.

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Multiparty Computation for Dishonest Majority: From Passive to Active Security at Low Cost

Cited by 48 publications

References 23 publications

Semi-homomorphic Encryption and Multiparty Computation

Semi-homomorphic Encryption and Multiparty Computation

5PM: Secure Pattern Matching

Oblivious and fair server-aided two-party computation

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