Protocols for secure computations

Yao, Xin

doi:10.1109/sfcs.1982.38

Cited by 3,077 publications

(2,089 citation statements)

References 4 publications

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“…The problem of multiparty computation (MPC) dates back to the papers by Yao [Yao82] and Goldreich et al [GMW87]. What was proved there was basically that a collection of n parties can efficiently compute the value of an n-input function, such that everyone learns the correct result, but no other new information.…”

Section: Introductionmentioning

confidence: 99%

Multiparty Computation from Threshold Homomorphic Encryption

Cramer¹,

Damgård²,

Nielsen³

2001

Lecture Notes in Computer Science

395

241

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Abstract. We introduce a new approach to multiparty computation (MPC) basing it on homomorphic threshold crypto-systems. We show that given keys for any sufficiently efficient system of this type, general MPC protocols for n parties can be devised which are secure against an active adversary that corrupts any minority of the parties. The total number of bits broadcast is O(nk|C|), where k is the security parameter and |C| is the size of a (Boolean) circuit computing the function to be securely evaluated. An earlier proposal by Franklin and Haber with the same complexity was only secure for passive adversaries, while all earlier protocols with active security had complexity at least quadratic in n. We give two examples of threshold cryptosystems that can support our construction and lead to the claimed complexities.

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Section: Introductionmentioning

confidence: 99%

Multiparty Computation from Threshold Homomorphic Encryption

Cramer¹,

Damgård²,

Nielsen³

2001

Lecture Notes in Computer Science

395

241

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“…Secure multi-party computation (MPC) was introduced by Yao in [1]. It deals with the problem of securely computing an arbitrary function f over the private inputs of n players.…”

Section: Introductionmentioning

confidence: 99%

Secure Two-Party Context Free Language Recognition

Singh

Barman

Shukla

2005

Distributed Computing and Internet Technology

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Abstract. The growth of the internet provides opportunities for cooperative computation, it also requires development of protocols that can accomplish this task among mutually untrusting parties. The aim is to develop methods which ensure both the correct evaluation of the function and privacy of individual inputs. Multiparty Computation protocols help to achieve the aim without using a trusted third party.In this paper we consider the problem of context-free language recognition in a two-party setting. Alice has the description of a context-free language L while Bob has a secret string whose membership in L is to be checked. Neither Alice nor Bob is ready to disclose his/her input to the other. Here we propose a protocol which accomplishes secure two party context-free language recognition. The novelty of this paper lies in the use of formal languages based approach for multiparty computations.

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“…Private computation was introduced by Yao [8]. He considered the problem under cryptographic assumptions.…”

Section: Introductionmentioning

confidence: 99%

Revealing Additional Information in Two-Party Computations

Jakoby

Liśkiewicz

2005

Lecture Notes in Computer Science

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Abstract.A two-argument function is computed privately by two parties if after the computation, no party should know anything about the other inputs except for what he is able to deduce from his own input and the function value. In [1] Bar-Yehuda, Chor, Kushilevitz, and Orlitsky give a complete characterisation of two-argument functions which can be computed privately (in the information-theoretical sense) in the Honest-But-Curious model and study protocols for "non-private" functions revealing as little information about the inputs as possible. The authors define a measure which determines for any function f the additional information E (f ) required for computing f and claim that f is privately-computable if and only if E (f ) = 0. In our paper we show that the characterisation is false: we give a privately-computable function f with E (f ) = 0 and another function g with E (g) = 0 that is not privately-computable. Moreover, we show some rather unexpected and strange properties of the measure for additional information given by Bar-Yehuda et al. and we introduce an alternative measure. We show that for this new measure the minimal leakage of information of randomized and deterministic protocols are equal. Finally, we present some general relations between the information gain of an optimal protocol and the communication complexity of a function.

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Protocols for secure computations

Cited by 3,077 publications

References 4 publications

Multiparty Computation from Threshold Homomorphic Encryption

Multiparty Computation from Threshold Homomorphic Encryption

Secure Two-Party Context Free Language Recognition

Revealing Additional Information in Two-Party Computations

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