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arXiv:quant-ph/0304112 · IEEE Conference on Computational Complexity (CCC)

Multiparty quantum coin flipping

Andris Ambainis, Harry Buhrman, Yevgeniy Dodis, Hein Röhrig

Published Nov 12, 2004• 47 citations
arXivHTMLPDF

Abstract

We investigate coin-flipping protocols for multiple parties in a quantum broadcast setting: (1) we propose and motivate a definition for quantum broadcast. Our model of quantum broadcast channel is new. (2) We discovered that quantum broadcast is essentially a combination of pairwise quantum channels and a classical broadcast channel. This is a somewhat surprising conclusion, but helps us in both our lower and upper bounds. (3) We provide tight upper and lower bounds on the optimal bias /spl epsiv/ of a coin which can be flipped by k parties of which exactly g parties are honest: for any 1 /spl les/ g /spl les/ k, /spl epsiv/ = 1/2 - /spl Theta/ (g/k). Thus, as long as a constant fraction of the players are honest, they can prevent the coin from being fixed with at least a constant probability. This result stands in sharp contrast with the classical setting, where no non-trivial coin-flipping is possible when g /spl les/ k/2.

DOI
10.1109/ccc.2004.1313848

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We investigate coin-flipping protocols for multiple parties in a quantum broadcast setting: (1) we propose and motivate a definition for quantum broadcast. Our model of quantum broadcast channel is new. (2) We discovered that quantum broadcast is essentially a combination of pairwise quantum channels and a classical broadcast channel. This is a somewhat surprising conclusion, but helps us in both our lower and upper bounds. (3) We provide tight upper and lower bounds on the optimal bias /spl epsiv/ of a coin which can be flipped by k parties of which exactly g parties are honest: for any 1 /spl les/ g /spl les/ k, /spl epsiv/ = 1/2 - /spl Theta/ (g/k). Thus, as long as a constant fraction of the players are honest, they can prevent the coin from being fixed with at least a constant probability. This result stands in sharp contrast with the classical setting, where no non-trivial coin-flipping is possible when g /spl les/ k/2.
We present a new protocol and two lower bounds for quantum coin flipping. In our protocol, no dishonest party can achieve one outcome with probability more than 0.75. Then, we show that our protocol is optimal for a certain type of quantum protocols. For arbitrary quantum protocols, we show that if a protocol achieves a bias of at most εεε, it must use at least Ω(log⁡log⁡1ε)Ω(\log \log \frac{1}ε)Ω(loglogε1​) rounds of communication. This implies that the parallel repetition fails for quantum coin flipping. (The bias of a protocol cannot be arbitrarily decreased by running several copies of it in parallel.)
Quantum coin flipping is a cryptographic primitive in which two or more parties that do not trust each other want establish a fair coin flip. These parties are not physically near each other and use quantum communication channels to interact. A quality of protocols is measured by the best possible cheating strategy, which is the solution of a complex semidefinite optimization problem. In this master thesis we show new explicit bounds in multiparty quantum coin flipping, we investigate how to explicitly formulate these problem in a standard form, we show that a fair coin flip results in the lowest possible bias and we determine more measures of the quality of a protocol. Furthermore, this master thesis presents a rigorous and detailed mathematical description of semidefinite optimization, quantum information theory and quantum coin flipping. This thesis also includes an article written together with J. Mulderij, T. Attema, I. Chiscop and F. Phillipson on distributed quantum computing. In this article, we pose new questions and formulate integer linear programs that solve to find optimal assignment of qubits to computers for a given network of quantum computers and quantum algorithm.
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.
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.
Coin flipping is one of the most fundamental tasks in cryptographic protocol design. Informally, a coin flipping protocol should guarantee both (1) Completeness: an honest execution of the protocol by both parties results in a fair coin toss, and (2) Security: a cheating party cannot increase the probability of its desired outcome by any significant amount. Since its introduction by Blum, coin flipping has occupied a central place in the theory of cryptographic protocols. In this paper, we explore what are the implications of the existence of secure coin flipping protocols for complexity theory. As exposited recently by Impagliazzo, surprisingly little is known about this question. Previous work has shown that if we interpret the Security property of coin flipping protocols very strongly, namely that nothing beyond a negligible bias by cheating parties is allowed, then one-way functions must exist. However, for even a slight weakening of this security property (for example that cheating parties cannot bias the outcome by any additive constant ε > 0), the only complexity-theoretic implication that was known was that PSPACE ⊈ BPP. We put forward a new attack to establish our main result, which shows that, informally speaking, the existence of any (weak) coin flipping protocol that prevents a cheating adversary from biasing the output by more than 1/4 - ε implies that NP ⊈ BPP. Furthermore, for constant-round protocols, we show that the existence of any (weak) coin flipping protocol that allows an honest party to maintain any noticeable chance of prevailing against a cheating party implies the existence of (infinitely often) one-way functions.