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

How Fair is Your Protocol? A Utility-based Approach to Protocol Optimality

Juan A. Garay, Jonathan I. Katz, Vassilis Zikas

Published Jan 1, 2015• 2 citations
OpenAlex

Abstract

In his seminal result, Cleve [STOC’86] established that secure distributed computation— guaranteeing fairness—is impossible in the presence of dishonest majorities. A generous number of proposals for relaxed notions of fairness ensued this seminal result, by weakening in various ways the desired security guarantees. While these works also suggest completeness results (i.e., the ability to design protocols which achieve their fairness notion), their assessment is typically of an all-or-nothing nature. That is, when presented with a protocol which is not designed to be fair according to their respective notion, they most likely would render it unfair and make no further statement about it. In this work we put forth a comparative approach to fairness. We present new intuitive notions that when presented with two arbitrary protocols, provide the means to answer the question “Which of the protocols is fairer? ” The basic idea is that we can use an appropriate utility function to express the preferences of an adversary who wants to break fairness. Thus, we can compare protocols with respect to how fair they are, placing them in a partial order according to this relative-fairness relation. After formulating such utility-based fairness notions, we turn to the question of finding optimal protocols—i.e., maximal elements in the above partial order. We investigate—and answer—this question for secure function evaluation, both in the two-party and multi-party settings. To our knowledge, the only other fairness notion providing some sort of comparative state-ment is that of 1/p-security (aka “partial fairness”) by Gordon and Katz [Eurocrypt’10]. We also show in this paper that for a special class of utilities our notion strictly implies 1/p-security. In addition, we fix a shortcoming of the definition which is exposed by our comparison, thus strengthening that result. Key words: Cryptographic protocols, secure multi-party computation, fairness, rational protocol design. 1

Related papers

How Fair is Your Protocol?

Juan A. Garay, Jonathan I. Katz, Björn Tackmann +1 more

Security of distributed cryptographic protocols usually requires privacy (inputs of the honest parties remain hidden), correctness (the adversary cannot improperly affect the outcome), and fairness (if the adversary learns the output, all honest parties do also). Cleve's seminal result (STOC '86) implies that satisfying these properties simultaneously is impossible in the presence of dishonest majorities, and led to several proposals for relaxed notions of fairness. While these works also suggest completeness results (i.e., the ability to design protocols which achieve their fairness notion), their assessment is typically of an all-or-nothing nature. In this work we put forth a new approach for defining relaxed fairness guarantees that allows for a quantitative comparison between protocols with regard to the level of fairness they achieve. The basic idea is to use an appropriate utility function to express the preferences of an adversary who wants to violate fairness. We also show optimal protocols with respect to our notion, in both the two-party and multi-party settings.

ACM Symposium on Principles of Distributed Computing (PODC)•Jul 17, 2015•22 citations

On fairness in secure computation

Jonathan I. Katz, Samuel Dov Gordon

Secure computation is a fundamental problem in modern cryptography in which multiple parties join to compute a function of their private inputs without revealing anything beyond the output of the function. A series of very strong results in the 1980’s demonstrated that any polynomial-time function can be computed while guaranteeing essentially every desired security property. The only exception is the fairness property, which states that no player should receive their output from the computation unless all players receive their output. While it was shown that fairness can be achieved whenever a majority of players are honest, it was also shown that fairness is impossible to achieve in general when half or more of the players are dishonest. Indeed, it was proven that even boolean XOR cannot be computed fairly by two parties. The fairness property is both natural and important, and as such it was one of the first questions addressed in modern cryptography (in the context of signature exchange). One contribution of this thesis is to survey the many approaches that have been used to guarantee different notions of partial fairness. We then revisit the topic of fairness within a modern security framework for secure computation. We demonstrate that, despite the strong impossibility result mentioned above, certain interesting functions can be computed fairly, even when half (or more) of the parties are malicious. We also provide a new notion of partial fairness, demonstrate feasibility of achieving this notion for a large class of functions, and show impossibility for certain functions outside this class. We consider fairness in the presence of rational adversaries, and, finally, we study the difficulty of achieving fairness by exploring how much external help is necessary for providing fair secure computation.

•Jan 1, 2010•10 citations

Partial Fairness in Secure Two-Party Computation.

Steven Gordon, Jonathan I. Katz

A seminal result of Cleve (STOC ’86) is that, in general, complete fairness is impossible to achieve in two-party computation. In light of this, various techniques for obtaining partial fairness have been suggested in the literature. We propose a definition of partial fairness within the standard real-/ideal-world paradigm that addresses deficiencies of prior definitions. also show broad feasibility results with respect to our definition: partial fairness is possible for any (randomized) functionality f: X × Y → Z 1 × Z 2 at least one of whose domains or ranges is polynomial in size. Our protocols are always private, and when one of the domains has polynomial size our protocols also simultaneously achieve the usual notion of security with abort. In contrast to some prior work, we rely on standard assumptions only. We also show that, as far as general feasibility is concerned, our results are optimal. Specifically, there exist functions with super-polynomial domains and ranges for which it is impossible to achieve our definition.

•Jan 1, 2008•8 citations

Secure Multiparty Computation with Partial Fairness

Amos Beimel, Eran Omri, Ilan Orlov

A protocol for computing a functionality is secure if an adversary in this protocol cannot cause more harm than in an ideal computation where parties give their inputs to a trusted party which returns the output of the functionality to all parties. In particular, in the ideal model such computation is fair -- all parties get the output. Cleve (STOC 1986) proved that, in general, fairness is not possible without an honest majority. To overcome this impossibility, Gordon and Katz (Eurocrypt 2010) suggested a relaxed definition -- 1/p-secure computation -- which guarantees partial fairness. For two parties, they construct 1/p-secure protocols for functionalities for which the size of either their domain or their range is polynomial (in the security parameter). Gordon and Katz ask whether their results can be extended to multiparty protocols. We study 1/p-secure protocols in the multiparty setting for general functionalities. Our main result is constructions of 1/p-secure protocols when the number of parties is constant provided that less than 2/3 of the parties are corrupt. Our protocols require that either (1) the functionality is deterministic and the size of the domain is polynomial (in the security parameter), or (2) the functionality can be randomized and the size of the range is polynomial. If the size of the domain is constant and the functionality is deterministic, then our protocol is efficient even when the number of parties is O(log log n) (where n is the security parameter). On the negative side, we show that when the number of parties is super-constant, 1/p-secure protocols are not possible when the size of the domain is polynomial.

arXiv:1011.5567•Nov 25, 2010•0 citations

Fair Computation with Rational Players.

Adam Groce, Jonathan I. Katz

We consider the problem of fair two-party computation, where fairness (informally) means that both parties should learn the correct output. A seminal result of Cleve (STOC 1986) shows that fairness is, in general, impossible to achieve for malicious parties. Here, we treat the parties as rational and seek to understand what can be done. Asharov et al. (Eurocrypt 2011) recently considered this problem and showed impossibility of rational fair computation for a particular function and a particular set of utilities. We observe, however, that in their setting the parties have no incentive to compute the function even in an ideal world where fairness is guaranteed. Revisiting the problem, we show that rational fair computation is possible (for arbitrary functions and utilities) as long as the parties have a strict incentive to compute the function in the ideal world. This gives a new example where game theory can be used to circumvent impossibility results in cryptography.

•Jan 1, 2011•1 citation

Fairness in Secure Two-Party Computation with Rational Players.

Arpita Maitra, Goutam Paul, Asim Kumar Pal

A seminal result of Cleve (STOC 1986) showed that fairness, in general, is impossible to achieve in case of two-party computation if one of them is malicious. Later, Gordon et al. (STOC 2008) observed that there exist some functions for which fairness can be achieved even though one of the two parties is malicious. One of the functions considered by Gordon et al. is exactly the millionaires ’ problem (Yao, FOCS 1982) or, equivalently, the ‘greater-than’ function. Interestingly, Gordon et al. (JACM, 2011) showed that any function over polynomial-size domains which does not contain an “embedded XOR ” can be converted into the greater than function. In the same paper, they also demonstrated feasibility for certain functions that do contain an embedded XOR. In this paper, we revisit both the classes of two-party computation under rational players for the first time. We show that Gordon’s protocols no longer remain fair when the players are rational. Further, we design two protocols, one without embedded XOR (the greater-than function) and the other with embedded XOR, and show that with rational players, our protocols achieve fairness under suitable choice of parameters.

•Jan 1, 2015•0 citations
In his seminal result, Cleve [STOC’86] established that secure distributed computation— guaranteeing fairness—is impossible in the presence of dishonest majorities. A generous number of proposals for relaxed notions of fairness ensued this seminal result, by weakening in various ways the desired security guarantees. While these works also suggest completeness results (i.e., the ability to design protocols which achieve their fairness notion), their assessment is typically of an all-or-nothing nature. That is, when presented with a protocol which is not designed to be fair according to their respective notion, they most likely would render it unfair and make no further statement about it. In this work we put forth a comparative approach to fairness. We present new intuitive notions that when presented with two arbitrary protocols, provide the means to answer the question “Which of the protocols is fairer? ” The basic idea is that we can use an appropriate utility function to express the preferences of an adversary who wants to break fairness. Thus, we can compare protocols with respect to how fair they are, placing them in a partial order according to this relative-fairness relation. After formulating such utility-based fairness notions, we turn to the question of finding optimal protocols—i.e., maximal elements in the above partial order. We investigate—and answer—this question for secure function evaluation, both in the two-party and multi-party settings. To our knowledge, the only other fairness notion providing some sort of comparative state-ment is that of 1/p-security (aka “partial fairness”) by Gordon and Katz [Eurocrypt’10]. We also show in this paper that for a special class of utilities our notion strictly implies 1/p-security. In addition, we fix a shortcoming of the definition which is exposed by our comparison, thus strengthening that result. Key words: Cryptographic protocols, secure multi-party computation, fairness, rational protocol design. 1
Security of distributed cryptographic protocols usually requires privacy (inputs of the honest parties remain hidden), correctness (the adversary cannot improperly affect the outcome), and fairness (if the adversary learns the output, all honest parties do also). Cleve's seminal result (STOC '86) implies that satisfying these properties simultaneously is impossible in the presence of dishonest majorities, and led to several proposals for relaxed notions of fairness. While these works also suggest completeness results (i.e., the ability to design protocols which achieve their fairness notion), their assessment is typically of an all-or-nothing nature. In this work we put forth a new approach for defining relaxed fairness guarantees that allows for a quantitative comparison between protocols with regard to the level of fairness they achieve. The basic idea is to use an appropriate utility function to express the preferences of an adversary who wants to violate fairness. We also show optimal protocols with respect to our notion, in both the two-party and multi-party settings.
Secure computation is a fundamental problem in modern cryptography in which multiple parties join to compute a function of their private inputs without revealing anything beyond the output of the function. A series of very strong results in the 1980’s demonstrated that any polynomial-time function can be computed while guaranteeing essentially every desired security property. The only exception is the fairness property, which states that no player should receive their output from the computation unless all players receive their output. While it was shown that fairness can be achieved whenever a majority of players are honest, it was also shown that fairness is impossible to achieve in general when half or more of the players are dishonest. Indeed, it was proven that even boolean XOR cannot be computed fairly by two parties. The fairness property is both natural and important, and as such it was one of the first questions addressed in modern cryptography (in the context of signature exchange). One contribution of this thesis is to survey the many approaches that have been used to guarantee different notions of partial fairness. We then revisit the topic of fairness within a modern security framework for secure computation. We demonstrate that, despite the strong impossibility result mentioned above, certain interesting functions can be computed fairly, even when half (or more) of the parties are malicious. We also provide a new notion of partial fairness, demonstrate feasibility of achieving this notion for a large class of functions, and show impossibility for certain functions outside this class. We consider fairness in the presence of rational adversaries, and, finally, we study the difficulty of achieving fairness by exploring how much external help is necessary for providing fair secure computation.
A seminal result of Cleve (STOC ’86) is that, in general, complete fairness is impossible to achieve in two-party computation. In light of this, various techniques for obtaining partial fairness have been suggested in the literature. We propose a definition of partial fairness within the standard real-/ideal-world paradigm that addresses deficiencies of prior definitions. also show broad feasibility results with respect to our definition: partial fairness is possible for any (randomized) functionality f: X × Y → Z 1 × Z 2 at least one of whose domains or ranges is polynomial in size. Our protocols are always private, and when one of the domains has polynomial size our protocols also simultaneously achieve the usual notion of security with abort. In contrast to some prior work, we rely on standard assumptions only. We also show that, as far as general feasibility is concerned, our results are optimal. Specifically, there exist functions with super-polynomial domains and ranges for which it is impossible to achieve our definition.
A protocol for computing a functionality is secure if an adversary in this protocol cannot cause more harm than in an ideal computation where parties give their inputs to a trusted party which returns the output of the functionality to all parties. In particular, in the ideal model such computation is fair -- all parties get the output. Cleve (STOC 1986) proved that, in general, fairness is not possible without an honest majority. To overcome this impossibility, Gordon and Katz (Eurocrypt 2010) suggested a relaxed definition -- 1/p-secure computation -- which guarantees partial fairness. For two parties, they construct 1/p-secure protocols for functionalities for which the size of either their domain or their range is polynomial (in the security parameter). Gordon and Katz ask whether their results can be extended to multiparty protocols. We study 1/p-secure protocols in the multiparty setting for general functionalities. Our main result is constructions of 1/p-secure protocols when the number of parties is constant provided that less than 2/3 of the parties are corrupt. Our protocols require that either (1) the functionality is deterministic and the size of the domain is polynomial (in the security parameter), or (2) the functionality can be randomized and the size of the range is polynomial. If the size of the domain is constant and the functionality is deterministic, then our protocol is efficient even when the number of parties is O(log log n) (where n is the security parameter). On the negative side, we show that when the number of parties is super-constant, 1/p-secure protocols are not possible when the size of the domain is polynomial.
We consider the problem of fair two-party computation, where fairness (informally) means that both parties should learn the correct output. A seminal result of Cleve (STOC 1986) shows that fairness is, in general, impossible to achieve for malicious parties. Here, we treat the parties as rational and seek to understand what can be done. Asharov et al. (Eurocrypt 2011) recently considered this problem and showed impossibility of rational fair computation for a particular function and a particular set of utilities. We observe, however, that in their setting the parties have no incentive to compute the function even in an ideal world where fairness is guaranteed. Revisiting the problem, we show that rational fair computation is possible (for arbitrary functions and utilities) as long as the parties have a strict incentive to compute the function in the ideal world. This gives a new example where game theory can be used to circumvent impossibility results in cryptography.
A seminal result of Cleve (STOC 1986) showed that fairness, in general, is impossible to achieve in case of two-party computation if one of them is malicious. Later, Gordon et al. (STOC 2008) observed that there exist some functions for which fairness can be achieved even though one of the two parties is malicious. One of the functions considered by Gordon et al. is exactly the millionaires ’ problem (Yao, FOCS 1982) or, equivalently, the ‘greater-than’ function. Interestingly, Gordon et al. (JACM, 2011) showed that any function over polynomial-size domains which does not contain an “embedded XOR ” can be converted into the greater than function. In the same paper, they also demonstrated feasibility for certain functions that do contain an embedded XOR. In this paper, we revisit both the classes of two-party computation under rational players for the first time. We show that Gordon’s protocols no longer remain fair when the players are rational. Further, we design two protocols, one without embedded XOR (the greater-than function) and the other with embedded XOR, and show that with rational players, our protocols achieve fairness under suitable choice of parameters.