【2h】

Cryptographic hashing using chaotic hydrodynamics

机译:使用混沌流体力学的密码学哈希

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摘要

Fluids may store and manipulate information, enabling complex applications ranging from digital logic gates to algorithmic self-assembly. While controllable hydrodynamic chaos has previously been observed in viscous fluids and harnessed for efficient mixing, its application to the manipulation of digital information has been sparsely investigated. We show that chaotic stirring of a viscous fluid naturally produces a characteristic signature of the stirring process in the arrangement of particles in the fluid, and that this signature directly satisfies the requirements for a cryptographic hash function. This includes strong divergence between similar stirring protocols’ hashes and avoidance of collisions (identical hashes from distinct stirs), which are facilitated by noninvertibility and a broad chaotic attractor that samples many points in the fluid domain. The hashing ability of the chaotic fluidic map implicates several unexpected mechanisms, including incomplete mixing at short time scales that produces a hyperuniform hash distribution. We investigate the dynamics of hashing using interparticle winding statistics, and find that hashing starts with large-scale winding of kinetically disjoint regions of the chaotic attractor, which gradually gives way to smaller scale braiding of single-particle trajectories. In addition to providing a physically motivated approach to implementing and analyzing deterministic chaotic maps for cryptographic applications, we anticipate that our approach has applications in microfluidic proof-of-work systems and characterizing large-scale turbulent flows from sparse tracer data.
机译:流体可以存储和操纵信息,从而实现从数字逻辑门到算法自组装的复杂应用。虽然以前已经在粘性流体中观察到可控的流体动力学混乱,并利用其来进行有效混合,但人们对其稀疏的数字信息处理应用进行了研究。我们表明,粘性流体的混沌搅拌自然会在流体中的颗粒排列中产生搅拌过程的特征性特征,并且该特征直接满足密码学哈希函数的要求。这包括相似的搅拌方案的哈希值之间的巨大差异以及避免碰撞(来自不同搅拌的相同哈希值),这是由于不可逆性和对流体域中许多点进行采样的宽泛的混沌吸引子而促进的。混沌流体图的散列能力暗示了几种意想不到的机制,包括在短时间尺度上的不完全混合,从而产生了超均匀的散列分布。我们使用粒子间缠绕统计数据研究哈希的动力学,发现哈希从混沌吸引子的动力学不相交区域的大规模缠绕开始,逐渐让位于单粒子轨迹的较小规模编织。除了提供一种物理动机的方法来实现和分析用于密码学应用的确定性混沌映射之外,我们还期望我们的方法可应用于微流体工作量证明系统并根据稀疏的示踪数据表征大规模湍流。

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