基于自编码器与<italic style="font-style: italic">K</italic>均值量化的可重构智能表面辅助密钥生成

李珍玲; 徐盼盼; 高强强; 李春国; 谭伟杰

doi:10.1631/FITEE.2400799

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基于自编码器与K均值量化的可重构智能表面辅助密钥生成

常规文章 | Updated：2025-09-04

- 基于自编码器与K均值量化的可重构智能表面辅助密钥生成
  Enhanced Publication
- Reconfigurable intelligent surface-aided secret key generation using an autoencoder and K-means quantization
- “在无线通信安全领域，提出了一种新的可重构智能表面辅助密钥生成方法，该方法使用自动编码器和K-means量化算法。该方法增强了信道随机性，有效地提取了随机比特，显著降低了密钥不一致率。仿真表明，在各种信噪比下，密钥生成率和密钥随机性表现优异。”
- 信息与电子工程前沿（英文） 2025年26卷第8期页码：1486-1500
- Affiliations：
  
  1.School of Mathematics and Statistics, Guizhou University, Guiyang 550025, China
  2.State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China
  3.School of Computer Science and Technology, Guizhou University, Guiyang 550025, China
  4.School of Information Science and Engineering, Southeast University, Nanjing 212013, China
- Author bio：
  
  ‡ Corresponding author
- Funds：
  
  National Natural Science Foundation of China(62361010);Cultivation Project of Guizhou University([2019]56);Major Scientific and Technological Special Project of Guizhou Province([2024]014)
- DOI：10.1631/FITEE.2400799
  中图分类号： TN918.4
- 收稿：2024-09-13，
  
  修回：2024-12-17，
  
  纸质出版：2025-08
- Accepted：
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李珍玲, 徐盼盼, 高强强, 等. 基于自编码器与K均值量化的可重构智能表面辅助密钥生成[J]. 信息与电子工程前沿（英文）, 2025,26(8):1486-1500.

Zhenling LI, Panpan XU, Qiangqiang GAO, et al. Reconfigurable intelligent surface-aided secret key generation using an autoencoder and K-means quantization[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(8): 1486-1500.
李珍玲, 徐盼盼, 高强强, 等. 基于自编码器与K均值量化的可重构智能表面辅助密钥生成[J]. 信息与电子工程前沿（英文）, 2025,26(8):1486-1500. DOI： 10.1631/FITEE.2400799.

Zhenling LI, Panpan XU, Qiangqiang GAO, et al. Reconfigurable intelligent surface-aided secret key generation using an autoencoder and K-means quantization[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(8): 1486-1500. DOI： 10.1631/FITEE.2400799.

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基于自编码器与K均值量化的可重构智能表面辅助密钥生成

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

DOI：10.1631/FITEE.2400799