Spectral sensitivity near exceptional points as a resource for hardware encryption

Minye Yang, Liang Zhu, Qi Zhong, Ramy El-Ganainy () and Pai-Yen Chen ()
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Minye Yang: University of Illinois Chicago
Liang Zhu: University of Illinois Chicago
Qi Zhong: Michigan Technological University
Ramy El-Ganainy: Michigan Technological University
Pai-Yen Chen: University of Illinois Chicago

Nature Communications, 2023, vol. 14, issue 1, 1-10

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-36508-x

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