Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

A Zero-One Law for Secure Multi-Party Computation with Ternary Outputs (full version).

Gunnar Kreitz

Published Jan 1, 2011• 3 citations
OpenAlex

Abstract

Abstract. There are protocols to privately evaluate any function in the passive (honest-but-curious) setting assuming that the honest nodes are in majority. For some specific functions, protocols are known which remain secure even without an honest majority. The seminal work by Chor and Kushilevitz [7] gave a complete characterization of Boolean functions, showing that each Boolean function either requires an honest majority, or is such that it can be privately evaluated regardless of the number of colluding nodes. The problem of discovering the threshold for secure evaluation of more general functions remains an open problem. Towards a resolution, we provide a complete characterization of the security threshold for functions with three different outputs. Surprisingly, the zero-one law for Boolean functions extends to Z3, meaning that each function with range Z3 either requires honest majority or tolerates up to n colluding nodes. 1

Related papers

Complete Characterization of Fairness in Secure Two-Party Computation of Boolean Functions

Gilad Asharov, Amos Beimel, Nikolaos Makriyannis +1 more

Abstract. Fairness is a desirable property in secure computation; informally it means that if one party gets the output of the function, then all parties get the output. Alas, an implication of Cleve’s result [18th ACM Symposium on the Theory of Computing, 1986] is that when there is no honest majority, in particular in the important case of the two-party setting, there exist functions that cannot be computed with fairness. In a surprising result, Gordon et al. [18th ACM Symposium on the Theory of Computing, 2008; J. ACM, 58 (2011), 24] showed that some interesting functions can be computed with fairness in the two-party setting and reopened the question of understanding which Boolean functions can be computed with fairness, and which cannot. Our main result in this work is a complete characterization of the (symmetric) Boolean functions that can be computed with fairness in the two-party setting; this settles an open problem of Gordon et al. The statement of the characterization is quite simple: A function can be computed with fairness if and only if the all-one vector or the all-zero vector are in the affine span of either the rows or the columns of the matrix describing the function. This is true for both deterministic and randomized functions. To prove the possibility result, we modify the protocol of Gordon et al.; the resulting protocol computes with full security (and in particular with fairness) all functions that are computable with fairness. Complementing this result, we also show that any function that does not satisfy the aforementioned condition can be reduced to a fair sampling protocol, which, by Agrawal and Prabhakaran [ Advances in Cryptology – CRYPTO 2013, 2013], cannot be computed with fairness.

SIAM Journal on Computing•Sep 23, 2024•0 citations

Communication requirements for secure computation

Deepesh Data, Vinod M. Prabhakaran

The question of whether and how mutually distrusting parties can collaborate is a central theme in cryptography. The goal of secure function computation is to ensure that parties may correctly compute functions of their data without learning additional information. A remarkable result of Ben Or, Goldwasser, and Wigderson from 1988 shows that it is possible for parties connected by pairwise, private, noise-free links to compute functions with zero error and perfect information theoretic security provided the number of parties who may collude meets a certain threshold; specifically, if the colluders form a strict minority for the honest-but-curious model and they are strictly less than a third for the malicious model. In this paper we provide basic lowerbounds on the amount of communication required to compute with zero-error and perfect security in a three-party setting under the honest-but-curious model.

Allerton Conference on Communication, Control, and Computing•Oct 1, 2013•2 citations

Towards Characterizing Complete Fairness in Secure Two-Party Computation.

Gilad Asharov

The well known impossibility result of Cleve (STOC 1986) implies that in general it is impossible to securely compute a function with complete fairness without an honest majority. Since then, the accepted belief has been that nothing non-trivial can be computed with complete fairness in the two party setting. The surprising work of Gordon, Hazay, Katz and Lindell (STOC 2008) shows that this belief is false, and that there exist some non-trivial (deterministic, nite-domain) boolean functions that can be computed fairly. This raises the fundamental question of characterizing complete fairness in secure two-party computation. In this work we show that not only that some or few functions can be computed fairly, but rather an enormous number of functions can be computed fairly. In fact, almost all boolean functions with distinct domain sizes can be computed with complete fairness (for instance, more than 99:999 % of the boolean functions with domain sizes 31 30). The class of functions that is shown to be possible includes also rather involved and highly non-trivial tasks, such as set-membership, evaluation of a private (boolean) function, private matchmaking and set-disjointness.

•Jan 1, 2014•0 citations

Complete Fairness in Secure Two-Party Computation

Steven Gordon, Carmit Hazay, Jonathan I. Katz +1 more

In the setting of secure two-party computation, two mutually distrusting parties wish to compute some function of their inputs while preserving, to the extent possible, various security properties such as privacy, correctness, and more. One desirable property is fairness which guarantees, informally, that if one party receives its output, then the other party does too. Cleve [1986] showed that complete fairness cannot be achieved in general without an honest majority. Since then, the accepted folklore has been that nothing non-trivial can be computed with complete fairness in the two-party setting. We demonstrate that this folklore belief is false by showing completely fair protocols for various nontrivial functions in the two-party setting based on standard cryptographic assumptions. We first show feasibility of obtaining complete fairness when computing any function over polynomial-size domains that does not contain an “embedded XOR”; this class of functions includes boolean AND/OR as well as Yao’s “millionaires’ problem”. We also demonstrate feasibility for certain functions that do contain an embedded XOR, though we prove a lower bound showing that any completely fair protocol for such functions must have round complexity super-logarithmic in the security parameter. Our results demonstrate that the question of completely fair secure computation without an honest majority is far from closed.

Journal of the ACM•Dec 1, 2011•72 citations

Complete Fairness in Secure Two-Party Computation.

Steven Gordon, Carmit Hazay, Jonathan I. Katz +1 more

In the setting of secure two-party computation, two mutually distrusting parties wish to compute some function of their inputs while preserving, to the extent possible, various security properties such as privacy, correctness, and more. One desirable property is fairness which guarantees, informally, that if one party receives its output, then the other party does too. Cleve (STOC 1986) showed that complete fairness cannot be achieved in general without an honest majority. Since then, the accepted folklore has been that nothing non-trivial can be computed with complete fairness in the two-party setting, and the problem has been treated as closed since the late ’80s. In this paper, we demonstrate that this folklore belief is false by showing completely-fair protocols for various non-trivial functions in the two-party setting based on standard cryptographic assumptions. We first show feasibility of obtaining complete fairness when computing any function over polynomial-size domains that does not contain an “embedded XOR”; this class of functions includes boolean AND/OR as well as Yao’s “millionaires ’ problem”. We also demonstrate feasibility for certain functions that do contain an embedded XOR, and prove a lower bound showing that any completely-fair protocol for such functions must have round complexity super-logarithmic in the security parameter. Our results demonstrate that the question of completely-fair secure computation without an honest majority is far from closed.

•Jan 1, 2008•26 citations

Fairness in two-party computation: characterizing fair functions

Nikolaos Makriyannis

Secure two-party computation is a classic problem in cryptography. It involves two parties computing a function of their private inputs, and only revealing what the output suggests. Additional security requirements may include fairness, which states that either all parties receive output, or no one does. A seminal result from the 1980's demonstrates that fairness cannot be guaranteed for all functions, and only recently have certain functions been shown to be computable with fairness. The two results naturally give rise to a distinction between fair functions and unfair ones. In this work, we investigate the characterization of such functions in the two-party setting. In the end, we obtain a full characterization for Boolean functions, and we develop a number of useful techniques for characterizing arbitrary fair functions.

•Sep 20, 2016•1 citation
Abstract. There are protocols to privately evaluate any function in the passive (honest-but-curious) setting assuming that the honest nodes are in majority. For some specific functions, protocols are known which remain secure even without an honest majority. The seminal work by Chor and Kushilevitz [7] gave a complete characterization of Boolean functions, showing that each Boolean function either requires an honest majority, or is such that it can be privately evaluated regardless of the number of colluding nodes. The problem of discovering the threshold for secure evaluation of more general functions remains an open problem. Towards a resolution, we provide a complete characterization of the security threshold for functions with three different outputs. Surprisingly, the zero-one law for Boolean functions extends to Z3, meaning that each function with range Z3 either requires honest majority or tolerates up to n colluding nodes. 1
Abstract. Fairness is a desirable property in secure computation; informally it means that if one party gets the output of the function, then all parties get the output. Alas, an implication of Cleve’s result [18th ACM Symposium on the Theory of Computing, 1986] is that when there is no honest majority, in particular in the important case of the two-party setting, there exist functions that cannot be computed with fairness. In a surprising result, Gordon et al. [18th ACM Symposium on the Theory of Computing, 2008; J. ACM, 58 (2011), 24] showed that some interesting functions can be computed with fairness in the two-party setting and reopened the question of understanding which Boolean functions can be computed with fairness, and which cannot. Our main result in this work is a complete characterization of the (symmetric) Boolean functions that can be computed with fairness in the two-party setting; this settles an open problem of Gordon et al. The statement of the characterization is quite simple: A function can be computed with fairness if and only if the all-one vector or the all-zero vector are in the affine span of either the rows or the columns of the matrix describing the function. This is true for both deterministic and randomized functions. To prove the possibility result, we modify the protocol of Gordon et al.; the resulting protocol computes with full security (and in particular with fairness) all functions that are computable with fairness. Complementing this result, we also show that any function that does not satisfy the aforementioned condition can be reduced to a fair sampling protocol, which, by Agrawal and Prabhakaran [ Advances in Cryptology – CRYPTO 2013, 2013], cannot be computed with fairness.
The question of whether and how mutually distrusting parties can collaborate is a central theme in cryptography. The goal of secure function computation is to ensure that parties may correctly compute functions of their data without learning additional information. A remarkable result of Ben Or, Goldwasser, and Wigderson from 1988 shows that it is possible for parties connected by pairwise, private, noise-free links to compute functions with zero error and perfect information theoretic security provided the number of parties who may collude meets a certain threshold; specifically, if the colluders form a strict minority for the honest-but-curious model and they are strictly less than a third for the malicious model. In this paper we provide basic lowerbounds on the amount of communication required to compute with zero-error and perfect security in a three-party setting under the honest-but-curious model.
The well known impossibility result of Cleve (STOC 1986) implies that in general it is impossible to securely compute a function with complete fairness without an honest majority. Since then, the accepted belief has been that nothing non-trivial can be computed with complete fairness in the two party setting. The surprising work of Gordon, Hazay, Katz and Lindell (STOC 2008) shows that this belief is false, and that there exist some non-trivial (deterministic, nite-domain) boolean functions that can be computed fairly. This raises the fundamental question of characterizing complete fairness in secure two-party computation. In this work we show that not only that some or few functions can be computed fairly, but rather an enormous number of functions can be computed fairly. In fact, almost all boolean functions with distinct domain sizes can be computed with complete fairness (for instance, more than 99:999 % of the boolean functions with domain sizes 31 30). The class of functions that is shown to be possible includes also rather involved and highly non-trivial tasks, such as set-membership, evaluation of a private (boolean) function, private matchmaking and set-disjointness.
In the setting of secure two-party computation, two mutually distrusting parties wish to compute some function of their inputs while preserving, to the extent possible, various security properties such as privacy, correctness, and more. One desirable property is fairness which guarantees, informally, that if one party receives its output, then the other party does too. Cleve [1986] showed that complete fairness cannot be achieved in general without an honest majority. Since then, the accepted folklore has been that nothing non-trivial can be computed with complete fairness in the two-party setting. We demonstrate that this folklore belief is false by showing completely fair protocols for various nontrivial functions in the two-party setting based on standard cryptographic assumptions. We first show feasibility of obtaining complete fairness when computing any function over polynomial-size domains that does not contain an “embedded XOR”; this class of functions includes boolean AND/OR as well as Yao’s “millionaires’ problem”. We also demonstrate feasibility for certain functions that do contain an embedded XOR, though we prove a lower bound showing that any completely fair protocol for such functions must have round complexity super-logarithmic in the security parameter. Our results demonstrate that the question of completely fair secure computation without an honest majority is far from closed.
In the setting of secure two-party computation, two mutually distrusting parties wish to compute some function of their inputs while preserving, to the extent possible, various security properties such as privacy, correctness, and more. One desirable property is fairness which guarantees, informally, that if one party receives its output, then the other party does too. Cleve (STOC 1986) showed that complete fairness cannot be achieved in general without an honest majority. Since then, the accepted folklore has been that nothing non-trivial can be computed with complete fairness in the two-party setting, and the problem has been treated as closed since the late ’80s. In this paper, we demonstrate that this folklore belief is false by showing completely-fair protocols for various non-trivial functions in the two-party setting based on standard cryptographic assumptions. We first show feasibility of obtaining complete fairness when computing any function over polynomial-size domains that does not contain an “embedded XOR”; this class of functions includes boolean AND/OR as well as Yao’s “millionaires ’ problem”. We also demonstrate feasibility for certain functions that do contain an embedded XOR, and prove a lower bound showing that any completely-fair protocol for such functions must have round complexity super-logarithmic in the security parameter. Our results demonstrate that the question of completely-fair secure computation without an honest majority is far from closed.
Secure two-party computation is a classic problem in cryptography. It involves two parties computing a function of their private inputs, and only revealing what the output suggests. Additional security requirements may include fairness, which states that either all parties receive output, or no one does. A seminal result from the 1980's demonstrates that fairness cannot be guaranteed for all functions, and only recently have certain functions been shown to be computable with fairness. The two results naturally give rise to a distinction between fair functions and unfair ones. In this work, we investigate the characterization of such functions in the two-party setting. In the end, we obtain a full characterization for Boolean functions, and we develop a number of useful techniques for characterizing arbitrary fair functions.