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arXiv:2104.08820 · ACM-SIAM Symposium on Discrete Algorithms (SODA)

Fair Coin Flipping: Tighter Analysis and the Many-Party Case

Niv Buchbinder, Iftach Haitner, Nissan Levi, Eliad Tsfadia

Published Jan 1, 2017• 24 citations
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Abstract

In a multi-party fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. In this work we focus on the case of dishonest majority, ie at least half of the parties can be corrupted. [19] [STOC 1986] has shown that in any m-round coin-flipping protocol the corrupted parties can bias the honest parties’ common output bit by Θ(1/m). For more than two decades the best known coin-flipping protocols against majority was the protocol of [9] [Manuscript 1985], who presented a t-party, m-round protocol with bias This was changed by the breakthrough result of [42] [TCC 2009], who constructed an m-round, two-party coin-flipping protocol with optimal bias Θ(1/m). Recently, [32] [STOC 14] constructed an m-round, three-party coin-flipping protocol with bias O(log3 m/m). Still for the case of more than three parties, against arbitrary number of corruptions, the best known protocol remained the protocol of [9]. We make a step towards eliminating the above gap, presenting a t-party, m-round coin-flipping protocol, with bias This improves upon the protocol of [9] for any t ≤ 1/2 · log log m, and in particular for t ∊ O(1), this yields an protocol. For the three-party case, this yields an protocol, improving over the the O(log3 m/m)-bias protocol of [32]. Our protocol generalizes that of [32], by presenting an appropriate “defense protocols” for the remaining parties to interact in, in the case that some parties abort or caught cheating ([32] only presented a two-party defense protocol, which limits their final protocol to handle three parties). We analyze our new protocols by presenting a new paradigm for analyzing fairness of coin-flipping protocols. We map the set of adversarial strategies that try to bias the honest parties outcome in the protocol to the set of the feasible solutions of a linear program. The gain each strategy achieves is the value of the corresponding solution. We then bound the the optimal value of the linear program by constructing a feasible solution to its dual.

DOI
10.1137/1.9781611974782.170

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Fair Coin Flipping: Tighter Analysis and the Many-Party Case

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Abstract In a multi-party fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some adversarial parties try to bias the output. In this work, we focus on the case of an arbitrary number of corrupted parties. Cleve [20] [STOC 1986] has shown that in any such m -round coin-flipping protocol, the corrupted parties can bias the honest parties’ common output bit by $$\Theta (1/m)$$ Θ ( 1 / m ) . For more than two decades, however, the best-known coin-flipping protocol was the one of Awerbuch, Blum, Chor, Goldwasser, and Micali [10] [Manuscript 1985], who presented a t -party, m -round protocol with bias $$\Theta (t/\sqrt{m})$$ Θ ( t / m ) . This was changed by the breakthrough result of Moran, Naor, and Segev [51] [Journal of Cryptology 2016], who constructed an m -round, two -party coin-flipping protocol with optimal bias $$\Theta (1/m)$$ Θ ( 1 / m ) . More recently, Haitner and Tsfadia [37] [SIAM Journal on Computing 2017] constructed an m -round, three -party coin-flipping protocol with bias $$O(\log ^3m / m)$$ O ( log 3 m / m ) . Still for the case of more than three parties, the best-known protocol remained the $$\Theta (t/\sqrt{m})$$ Θ ( t / m ) -bias protocol of [10]. We make a step toward eliminating the above gap, presenting a t -party, m -round coin-flipping protocol, with bias $$O\left( \frac{t^4 \cdot 2^t \cdot \sqrt{\log m}}{m^{1/2+1/(2^{t-1}-2)}}\right) $$ O t 4 · 2 t · log m m 1 / 2 + 1 / ( 2 t - 1 - 2 ) for any $$t\le \tfrac{1}{2} \cdot \operatorname {loglog}m$$ t ≤ 1 2 · loglog m . This improves upon the

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In a multiparty fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. Cleve [STOC 1986] has shown that in the case of dishonest majority (i.e., at least half of the parties can be corrupted), in any $m$-round coin-flipping protocol the corrupted parties can bias the honest parties' common output bit by $Ω(\frac1{m})$. For more than two decades the best known coin-flipping protocols against dishonest majority had bias $Θ(\frac{\ell}{\sqrt{m}})$, where $\ell$ is the number of corrupted parties. This was changed by a recent breakthrough result of Moran et al. [TCC 2009], who constructed an $m$-round, two-party coin-flipping protocol with optimal bias $Θ(\frac1{m})$. In a subsequent work, Beimel et al. [Crypto 2010] extended this result to the multiparty case in which less than $\frac23$ of the parties can be corrupted. Still for the case of $\frac23$ (or more) corrupted parties, the best known protocol had bias $Θ(\frac{\ell}{\sqrt{m}})$. In particular, this was the state of affairs for the natural three-party case. We make a step towards eliminating the above gap, presenting an $m$-round, three-party coin-flipping protocol, with bias $\frac{O(\log^3 m)}m$. Our approach (which we also apply for the two-party case) does not follow the "threshold round" paradigm used in the work of Moran et al. and Beimel et al., but rather is a variation of the majority protocol of Cleve, used to obtain the aforementioned $Θ(\frac{\ell}{\sqrt{m}})$-bias protocol.

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In a multiparty fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. Cleve [STOC 1986] has shown that in the case of dishonest majority (i.e., at least half of the parties can be corrupted), in any m-round coin-flipping protocol, the corrupted parties can bias the honest parties' common output bit by Ω(1/m). For more than two decades, the best known coin-flipping protocols against dishonest majority had bias [EQUATION], where ℓ is the number of corrupted parties. This was changed by a recent breakthrough result of Moran et al. [TCC 2009], who constructed an m-round, two-party coin-flipping protocol with optimal bias Θ(1/m). In a subsequent work, Beimel et al. [Crypto 2010] extended this result to the multiparty case in which less than 2/3 of the parties can be corrupted. Still for the case of 2/3 (or more) corrupted parties, the best known protocol had bias [EQUATION]. In particular, this was the state of affairs for the natural three-party case.

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In a multi-party fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. In this work we focus on the case of dishonest majority, ie at least half of the parties can be corrupted. [19] [STOC 1986] has shown that in any m-round coin-flipping protocol the corrupted parties can bias the honest parties’ common output bit by Θ(1/m). For more than two decades the best known coin-flipping protocols against majority was the protocol of [9] [Manuscript 1985], who presented a t-party, m-round protocol with bias This was changed by the breakthrough result of [42] [TCC 2009], who constructed an m-round, two-party coin-flipping protocol with optimal bias Θ(1/m). Recently, [32] [STOC 14] constructed an m-round, three-party coin-flipping protocol with bias O(log3 m/m). Still for the case of more than three parties, against arbitrary number of corruptions, the best known protocol remained the protocol of [9]. We make a step towards eliminating the above gap, presenting a t-party, m-round coin-flipping protocol, with bias This improves upon the protocol of [9] for any t ≤ 1/2 · log log m, and in particular for t ∊ O(1), this yields an protocol. For the three-party case, this yields an protocol, improving over the the O(log3 m/m)-bias protocol of [32]. Our protocol generalizes that of [32], by presenting an appropriate “defense protocols” for the remaining parties to interact in, in the case that some parties abort or caught cheating ([32] only presented a two-party defense protocol, which limits their final protocol to handle three parties). We analyze our new protocols by presenting a new paradigm for analyzing fairness of coin-flipping protocols. We map the set of adversarial strategies that try to bias the honest parties outcome in the protocol to the set of the feasible solutions of a linear program. The gain each strategy achieves is the value of the corresponding solution. We then bound the the optimal value of the linear program by constructing a feasible solution to its dual.
Abstract In a multi-party fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some adversarial parties try to bias the output. In this work, we focus on the case of an arbitrary number of corrupted parties. Cleve [20] [STOC 1986] has shown that in any such m -round coin-flipping protocol, the corrupted parties can bias the honest parties’ common output bit by Θ(1/m)\Theta (1/m)Θ(1/m) Θ ( 1 / m ) . For more than two decades, however, the best-known coin-flipping protocol was the one of Awerbuch, Blum, Chor, Goldwasser, and Micali [10] [Manuscript 1985], who presented a t -party, m -round protocol with bias Θ(t/m)\Theta (t/\sqrt{m})Θ(t/m​) Θ ( t / m ) . This was changed by the breakthrough result of Moran, Naor, and Segev [51] [Journal of Cryptology 2016], who constructed an m -round, two -party coin-flipping protocol with optimal bias Θ(1/m)\Theta (1/m)Θ(1/m) Θ ( 1 / m ) . More recently, Haitner and Tsfadia [37] [SIAM Journal on Computing 2017] constructed an m -round, three -party coin-flipping protocol with bias O(log⁡3m/m)O(\log ^3m / m)O(log3m/m) O ( log 3 m / m ) . Still for the case of more than three parties, the best-known protocol remained the Θ(t/m)\Theta (t/\sqrt{m})Θ(t/m​) Θ ( t / m ) -bias protocol of [10]. We make a step toward eliminating the above gap, presenting a t -party, m -round coin-flipping protocol, with bias O(t4⋅2t⋅log⁡mm1/2+1/(2t−1−2))O\left( \frac{t^4 \cdot 2^t \cdot \sqrt{\log m}}{m^{1/2+1/(2^{t-1}-2)}}\right) O(m1/2+1/(2t−1−2)t4⋅2t⋅logm​​) O t 4 · 2 t · log m m 1 / 2 + 1 / ( 2 t - 1 - 2 ) for any t≤12⋅loglog⁡mt\le \tfrac{1}{2} \cdot \operatorname {loglog}mt≤21​⋅loglogm t ≤ 1 2 · loglog m . This improves upon the
In a multiparty fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. Cleve [STOC 1986] has shown that in the case of dishonest majority (i.e., at least half of the parties can be corrupted), in any mmm-round coin-flipping protocol the corrupted parties can bias the honest parties' common output bit by Ω(1m)Ω(\frac1{m})Ω(m1​). For more than two decades the best known coin-flipping protocols against dishonest majority had bias Θ(ℓm)Θ(\frac{\ell}{\sqrt{m}})Θ(m​ℓ​), where ℓ\ellℓ is the number of corrupted parties. This was changed by a recent breakthrough result of Moran et al. [TCC 2009], who constructed an mmm-round, two-party coin-flipping protocol with optimal bias Θ(1m)Θ(\frac1{m})Θ(m1​). In a subsequent work, Beimel et al. [Crypto 2010] extended this result to the multiparty case in which less than 23\frac2332​ of the parties can be corrupted. Still for the case of 23\frac2332​ (or more) corrupted parties, the best known protocol had bias Θ(ℓm)Θ(\frac{\ell}{\sqrt{m}})Θ(m​ℓ​). In particular, this was the state of affairs for the natural three-party case. We make a step towards eliminating the above gap, presenting an mmm-round, three-party coin-flipping protocol, with bias O(log⁡3m)m\frac{O(\log^3 m)}mmO(log3m)​. Our approach (which we also apply for the two-party case) does not follow the "threshold round" paradigm used in the work of Moran et al. and Beimel et al., but rather is a variation of the majority protocol of Cleve, used to obtain the aforementioned Θ(ℓm)Θ(\frac{\ell}{\sqrt{m}})Θ(m​ℓ​)-bias protocol.
In a multiparty fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. Cleve [STOC 1986] has shown that in the case of dishonest majority (i.e., at least half of the parties can be corrupted), in any m-round coin-flipping protocol, the corrupted parties can bias the honest parties' common output bit by Ω(1/m). For more than two decades, the best known coin-flipping protocols against dishonest majority had bias [EQUATION], where ℓ is the number of corrupted parties. This was changed by a recent breakthrough result of Moran et al. [TCC 2009], who constructed an m-round, two-party coin-flipping protocol with optimal bias Θ(1/m). In a subsequent work, Beimel et al. [Crypto 2010] extended this result to the multiparty case in which less than 2/3 of the parties can be corrupted. Still for the case of 2/3 (or more) corrupted parties, the best known protocol had bias [EQUATION]. In particular, this was the state of affairs for the natural three-party case.
In a multiparty fair coin-flipping protocol, the parties output a common (close to) unbiased bit, even when some corrupted parties try to bias the output. Cleve [in Proceedings of the 20th Annual ACM Symposium on Theory of Computing (STOC), ACM, New York, 1986, pp. 364--369] has shown that in the case of dishonest majority (i.e., at least half of the parties can be corrupted), in any mmm-round coin-flipping protocol the corrupted parties can bias the honest parties' common output bit by Ω(1m)\Omega(\frac 1{m})Ω(m1​). For more than two decades the best known coin-flipping protocols against dishonest majority had bias Θ(ℓm)\Theta(\frac {\ell}{\sqrt{m}})Θ(m​ℓ​), where ℓ\ellℓ is the number of corrupted parties. This was changed by a recent breakthrough result of Moran, Naor, and Segev [in Theory of Cryptography, Lecture Notes in Comput. Sci. 5444, Springer, Berlin, 2009, pp. 1--18], who constructed an mmm-round, two-party coin-flipping protocol with optimal bias Θ(1m)\Theta(\frac 1 m)Θ(m1​). In a subsequent work, Beimel, Omri, and Orlov [in Proceedings of the 22nd Annual ACM Symposium on Theory of Computing (STOC), ACM, New York, 1990, pp. 503--513] extended this result to the multiparty case in which less than 23\frac2332​ of the parties can be corrupted. Still, for the case of 23\frac2332​ (or more) corrupted parties, the best known protocol had bias Θ(ℓm)\Theta(\frac {\ell}{\sqrt{m}})Θ(m​ℓ​). In particular, this was the state of affairs for the natural three-party case. We take a step toward eliminating the above gap, presenting an mmm-round, three-party coin-flipping protocol, with bias O(log⁡3m)m\frac{O(\log^3 m)}mmO(log3m)​. Our approach (which we also apply to the two-party case) does not follow the “threshold round" paradigm used in the work of Moran, Naor, and Segev and Beimel, Omri, and Orlov but rather is a variation of the majority protocol of Cleve used to obtain the aforementioned Θ(ℓm)\Theta(\frac {\ell}{\sqrt{m}})Θ(m​ℓ​)-bias protocol.
We address one of the foundational problems in cryptography: the bias of coin-\nipping pro-tocols. Coin-\nipping protocols allow mutually distrustful parties to generate a common unbiased random bit, guaranteeing that even if one of the parties is malicious, it cannot signicantly bias the output of the honest party. A classical result by Cleve [STOC '86] showed that for any two-party r-round coin-\nipping protocol there exists an efficient adversary that can bias the output of the honest party by Ω(1=r). However, the best previously known protocol only guarantees O(1= p r) bias, and the question of whether Cleve's bound is tight has remained open for more than twenty years. In this paper we establish the optimal trade-off between the round complexity and the bias of two-party coin-\nipping protocols. Under standard assumptions (the existence of oblivious transfer), we show that Cleve's lower bound is tight: we construct an r-round protocol with bias O(1=r).
In his seminal work, Cleve [STOC '86] has proved that any rrr-round coin-flipping protocol can be efficiently biased by Θ(1/r)Θ(1/r)Θ(1/r). This lower bound was met for the two-party case by Moran, Naor, and Segev [Journal of Cryptology '16], and the three-party case (up to a polylogpolylogpolylog factor) by Haitner and Tsfadi [SICOMP '17], and was approached for nnn-party protocols when n<loglogrn< loglog rn<loglogr by Buchbinder, Haitner, Levi, and Tsfadia [SODA '17]. For n>loglogrn> loglog rn>loglogr, however, the best bias for nnn-party coin-flipping protocols remains O(n/r)O(n/\sqrt{r})O(n/r​) achieved by the majority protocol of Awerbuch, Blum, Chor, Goldwasser, and Micali [Manuscript '85]. Our main result is a tighter lower bound on the bias of coin-flipping protocols, showing that, for every constant ε>0ε>0ε>0, an rεr^εrε-party rrr-round coin-flipping protocol can be efficiently biased by Ω~(1/r)\widetildeΩ(1/\sqrt{r})Ω(1/r​). As far as we know, this is the first improvement of Cleve's bound, and is only n=rεn=r^εn=rε (multiplicative) far from the aforementioned upper bound of Awerbuch et al.