Optics and Precision Engineering, Volume. 33, Issue 3, 486(2025)
Secret key extraction from atmospheric wireless optical channels by combing with generative adversarial network
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Fig. 6. Trend plot of MSE with SNR for legitimate parties generated data using SMA， DNN， GAN， CNN-GRU and proposed model
Fig. 7. Sequence segments of Alice's and Bob's received signals and extracted channel features using proposed model
Fig. 8. Trend plot of KDR variation with SNR for Alice and Bob by quantizing generated key without or with channel feature estimation
Table 1. Algorithmic complexity of different feature estimation methods
View tableView in ArticleTable 1. Algorithmic complexity of different feature estimation methods
Method Params/K FLOPs/K SMA 0.01 0.04 DNN 8.4 16.5 GAN 9.9 18.8 CNN-GRU 11.2 18.9 Proposed 62.6 68.9
Table 2. NIST test results of different quantization algorithms for generating shared key
View tableView in ArticleTable 2. NIST test results of different quantization algorithms for generating shared key
Test P-value Frequency 0.739 918 Block frequency 0.534 146 Runs 0.350 485 Longest runs 0.534 146 Binary matrix rank 0.213 309 Discrete fourier transform 0.035 174 Nonoverlapping template 0.525 940 Overlapping template 0.066 882 Linear complexity 0.437 274 Serial 0.534 146 0.437 274 Cumulative sums 0.739 918 0.834 308
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Zhuozhan TIAN, Chunyi CHEN, Xiaojuan HU, Haiyang YU, Yanfeng LI, Fang WANG. Secret key extraction from atmospheric wireless optical channels by combing with generative adversarial network[J]. Optics and Precision Engineering, 2025, 33(3): 486
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Received: Sep. 13, 2024
Accepted: --
Published Online: Apr. 30, 2025
The Author Email: Chunyi CHEN (chenchunyi@hotmail.com)
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