A Stable Hash Function Based on Parity-Dependent Quantum Walks With Memory (August 2023)

Qing Zhou;Xueming Tang;Songfeng Lu;Hao Yang
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Abstract

In this article, we develop a generic controlled alternate quantum walk model by combining parity-dependent quantum walks with distinct arbitrary memory lengths and propose a hash function (called QHFM-P) based on this model. The statistical properties of the proposed scheme are stable with respect to the coin parameters of the underlying controlled quantum walks, and with certain parameter values, the collision resistance property of QHFM-P is better than that of the state-of-the-art hash functions based on discrete quantum walks. Moreover, the proposed hash function can also maintain near-ideal statistical performance when the input message is of small length. In addition, we derive a type of inappropriate initial states of hash functions based on 1-D one-particle quantum walks (with ordinary shift operator) on cycles, with which all messages will be mapped to the same hash value, regardless of the angles adopted by the coin parameters.
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基于内存奇偶校验量子漫步的稳定哈希函数(2023 年 8 月)
在本文中,我们通过将奇偶校验依赖的量子行走与不同的任意记忆长度相结合,建立了一种通用的受控交替量子行走模型,并基于该模型提出了一种哈希函数(称为 QHFM-P)。所提方案的统计特性与底层受控量子漫步的硬币参数有关,而且在特定参数值下,QHFM-P 的抗碰撞特性优于基于离散量子漫步的最先进哈希函数。此外,当输入信息长度较小时,所提出的哈希函数也能保持接近理想的统计性能。此外,我们还推导出了一种基于循环上的一维单粒子量子行走(带普通移位算子)的哈希函数的不恰当初始状态,无论硬币参数采用何种角度,所有信息都将映射到相同的哈希值。
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