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Asynchronous Multiparty Computation with Linear Communication Complexity

机译:具有线性通信复杂性的异步多方计算

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Secure multiparty computation (MPC) allows a set of n parties to securely compute a function of their private inputs against an adversary corrupting up to t parties. Over the previous decade, the communication complexity of synchronous MPC protocols could be improved to O(n) per multiplication, for various settings. However, designing an asynchronous MPC (AMPC) protocol with linear communication complexity was not achieved so far. We solve this open problem by presenting two AMPC protocols with the corruption threshold t < n/4. Our first protocol is statistically secure (i.e. involves a negligible error) in a completely asynchronous setting and improves the communication complexity of the previous best AMPC protocol in the same setting by a factor of θ(n). Our second protocol is perfectly secure (i.e. error free) in a hybrid setting, where one round of communication is assumed to be synchronous, and improves the communication complexity of the previous best AMPC protocol in the hybrid setting by a factor of θ(n~2). Like other efficient MPC protocols, we employ Beaver's circuit randomization approach (Crypto '91) and prepare shared random multiplication triples. However, in contrast to previous protocols where triples are prepared by first generating two random shared values which are then multiplied distributively, in our approach each party prepares its own multiplication triples. Given enough such shared triples (potentially partially known to the adversary), we develop a method to extract shared triples unknown to the adversary, avoiding communication-intensive multiplication protocols. This leads to a framework of independent interest.
机译:安全多方计算(MPC)允许一组n个参与者安全地计算其私人输入的功能,以防对手破坏多达t个参与者。在过去的十年中,对于各种设置,同步MPC协议的通信复杂性可以提高到每个乘法O(n)。但是,到目前为止,尚未实现设计具有线性通信复杂性的异步MPC(AMPC)协议。通过提出两种腐败阈值t <n / 4的AMPC协议,我们解决了这个开放性问题。我们的第一个协议在完全异步的设置中在统计上是安全的(即涉及可忽略的错误),并且在相同设置中将以前最佳AMPC协议的通信复杂度提高了θ(n)。我们的第二个协议在混合环境中是完全安全的(即无错误),其中假设一轮通信是同步的,并且将混合环境中以前最佳AMPC协议的通信复杂度提高了θ(n〜 2)。像其他有效的MPC协议一样,我们采用Beaver的电路随机化方法(Crypto '91)并准备共享的随机乘法三元组。但是,与以前的协议相反,在三元组中,首先生成两个随机共享值,然后将它们进行分布乘积,然后在我们的方法中,每一方都准备自己的乘法三元组。给定足够多的此类共享三元组(可能是对手部分已知的),我们开发了一种方法来提取对手未知的共享三元组,从而避免了通信密集的乘法协议。这导致了一个独立利益的框架。

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