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异常点附近的光谱灵敏度可作为硬件加密的资源。

Spectral sensitivity near exceptional points as a resource for hardware encryption.

机构信息

Department of Electrical and Computer Engineering, University of Illinois Chicago, Chicago, IL, 60607, USA.

Department of Physics, Michigan Technological University, Houghton, MI, 49931, USA.

出版信息

Nat Commun. 2023 Feb 28;14(1):1145. doi: 10.1038/s41467-023-36508-x.

Abstract

The spectral sensitivity near exceptional points (EPs) has been recently explored as an avenue for building sensors with enhanced sensitivity. However, to date, it is not clear whether this class of sensors does indeed outperform traditional sensors in terms of signal-to-noise ratio. In this work, we investigate the spectral sensitivity associated with EPs under a different lens and propose to utilize it as a resource for hardware security. In particular, we introduce a physically unclonable function (PUF) based on analogue electronic circuits that benefit from the drastic eigenvalues bifurcation near a divergent exceptional point to enhance the stochastic entropy caused by inherent parameter fluctuations in electronic components. This in turn results in a perfect entropy source for the generation of encryption keys encoded in analog electrical signals. This lightweight and robust analog-PUF structure may lead to a variety of unforeseen securities and anti-counterfeiting applications in radio-frequency fingerprinting and wireless communications.

摘要

在异常点 (EP) 附近的光谱灵敏度最近被探索为构建具有增强灵敏度的传感器的途径。然而,迄今为止,尚不清楚这类传感器在信噪比方面是否确实优于传统传感器。在这项工作中,我们从不同的角度研究了与 EP 相关的光谱灵敏度,并提出将其用作硬件安全的资源。具体来说,我们引入了一种基于模拟电子电路的物理不可克隆函数 (PUF),该函数利用发散异常点附近的特征值分叉来增强由电子元件固有参数波动引起的随机熵。这反过来又为在模拟电信号中编码的加密密钥的生成提供了完美的熵源。这种轻量级和稳健的模拟 PUF 结构可能会在射频指纹识别和无线通信领域引发各种意想不到的安全和防伪应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e42/9974995/a8471137fb0f/41467_2023_36508_Fig1_HTML.jpg

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