论文标题
关于量子零知识的并发组成
On the Concurrent Composition of Quantum Zero-Knowledge
论文作者
论文摘要
我们研究了在并发组成设置中针对量子多项式时间验证者(称为量子零知识)的零知识安全性的概念。尽管在经典环境中进行了广泛的研究,但几乎没有研究量子设置中的并发组成。我们开始对并发量子零知识的正式研究。我们的结果如下: -NP和QMA结合的并发QZK:假设量词后单向函数,在有限的并发设置中存在NP的量子零知识证明系统。在这种情况下,我们先验修复了可以同时与供者交互的验证者的数量。在相同的假设下,我们还表明,在有限的并发设置中存在QMA的量子零知识证明系统。 - 知识的量化证明:假设使用错误的学习量子硬度(QLWE),存在一个有限的并发零知识证明系统,以满足NP满足知识属性的量子证明。我们的提取机制同时允许提取概率可忽略接近接受概率(可萃取性),还可以确保提取后的供者在与验证者相互作用后统计上接近供摊子的状态(模拟性)。 [Unruh eurocrypt'12]及其所有后续工作的开创性工作满足了较弱的可萃取性属性,并且没有实现可相似性。我们的结果提供了比先前的工作更好的QMA的量子知识系统证明。
We study the notion of zero-knowledge secure against quantum polynomial-time verifiers (referred to as quantum zero-knowledge) in the concurrent composition setting. Despite being extensively studied in the classical setting, concurrent composition in the quantum setting has hardly been studied. We initiate a formal study of concurrent quantum zero-knowledge. Our results are as follows: -Bounded Concurrent QZK for NP and QMA: Assuming post-quantum one-way functions, there exists a quantum zero-knowledge proof system for NP in the bounded concurrent setting. In this setting, we fix a priori the number of verifiers that can simultaneously interact with the prover. Under the same assumption, we also show that there exists a quantum zero-knowledge proof system for QMA in the bounded concurrency setting. -Quantum Proofs of Knowledge: Assuming quantum hardness of learning with errors (QLWE), there exists a bounded concurrent zero-knowledge proof system for NP satisfying quantum proof of knowledge property. Our extraction mechanism simultaneously allows for extraction probability to be negligibly close to acceptance probability (extractability) and also ensures that the prover's state after extraction is statistically close to the prover's state after interacting with the verifier (simulatability). The seminal work of [Unruh EUROCRYPT'12], and all its followups, satisfied a weaker version of extractability property and moreover, did not achieve simulatability. Our result yields a proof of quantum knowledge system for QMA with better parameters than prior works.