JZUS - Journal of Zhejiang University SCIENCE

Frontiers of Information Technology & Electronic Engineering

Accepted manuscript available online (unedited version)

Reconfigurable intelligent surface-aided secret key generation using autoencoder and K-means quantization

Author(s): Zhenling LI^†¹, Panpan XU¹, Qiangqiang GAO^2, ³, Chunguo LI⁴, Weijie TAN^‡^2, ³
Affiliation(s): ¹School of Mathematics and Statistics, GuiZhou University, Guiyang 550025, China; more
Corresponding email(s): wjtan@gzu.edu.cn
Key Words: Reconfigurable intelligent surface; Physical layer key generation; Quantization; Autoencoder

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Zhenling LI^†¹, Panpan XU¹, Qiangqiang GAO^2,³, Chunguo LI⁴, Weijie TAN^‡^2,³. Reconfigurable intelligent surface-aided secret key generation using autoencoder and K-means quantization[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2400799

@article{title="Reconfigurable intelligent surface-aided secret key generation using autoencoder and K-means quantization",
author="Zhenling LI^†¹, Panpan XU¹, Qiangqiang GAO^2,³, Chunguo LI⁴, Weijie TAN^‡^2,³",
journal="Frontiers of Information Technology & Electronic Engineering",
year="in press",
publisher="Zhejiang University Press & Springer",
doi="https://doi.org/10.1631/FITEE.2400799"
}

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%T Reconfigurable intelligent surface-aided secret key generation using autoencoder and K-means quantization
%A Zhenling LI^†¹
%A Panpan XU¹
%A Qiangqiang GAO^2
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%A Chunguo LI⁴
%A Weijie TAN^‡^2
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%J Frontiers of Information Technology & Electronic Engineering
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doi="https://doi.org/10.1631/FITEE.2400799"

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A1 - Weijie TAN^‡^{2
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doi="https://doi.org/10.1631/FITEE.2400799"

Abstract
Chinese Summary
Academic Network
Reviewer Comment

Abstract: In quasi-static wireless channel scenarios, the generation of physical layer keys faces the challenge of invariant spatial and temporal channel characteristics, resulting in a high key disagreement rate (KDR) and low key generation rate (KGR). To address these issues, this paper proposes a novel reconfigurable intelligent surface (RIS)-aided secret key generation approach using an autoencoder (AE) and K-means quantization algorithm. The proposed method utilizes channel state information (CSI) for channel estimation and dynamically adjusts the reflection coefficients of the RIS to create a rapidly fluctuating channel. This strategy enables the extraction of dynamic channel parameters, enhancing channel randomness. Additionally, by integrating the autoencoder with the K-means clustering quantization algorithm, the method efficiently extracts random bits from complex, ambiguous, and high-dimensional channel parameters, significantly reducing KDR. Simulation experiments demonstrate that, under various signal-to-noise ratios (SNRs), the proposed method performs excellently in terms of KGR and KDR. Additionally, the randomness of the generated keys is validated through the National Institute of Standards and Technology (NIST) test suite.

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