Experimental demonstration of integrated encryption and communication over optical fiber

As we enter the big data and artificial intelligence (AI) era, integrating security and communication over optical fiber has become a critical challenge. This urgency is driven by the need to protect vast amounts of sensitive data, ensuring privacy security across global high-capacity optical networks. Traditional secure communication methods often struggle to maintain high-capacity transmission performance while providing robust security. Here we propose an integrated encryption and communication (IEAC) framework, designed to maximize mutual information (MI) for legal users while minimizing it for potential eavesdroppers. Enabled by end-to-end deep learning, this holistic framework trains a random number-selected geometric constellation shaping scheme to optimize encryption processes and transmission quality simultaneously. The IEAC experiment system achieves a groundbreaking single-channel transmission rate of 1 Terabit per second (Tb/s) over a 1200-km fiber link, employing a 26-channel, 3.9 THz bandwidth, full C-band wavelength division multiplexing (WDM) configuration. The MI for eavesdroppers is under 0.2 bit per symbol where the regular value is near 4.0, ensuring secure transmission. The IEAC scheme offers a scalable, promising solution to meet the escalating demand for high-throughput, secure data transmission in the face of advancing big data and AI computational technologies.

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Institutions

Publication Details

Journal
National Science Review
Published
2025-04-02
DOI
https://doi.org/10.1093/nsr/nwaf112
Citations
5
Primary Topic
Optical Network Technologies
Type
article
Field-Weighted Citation Impact
3.65

Funders

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article

Experimental demonstration of integrated encryption and communication over optical fiber

Guoqing Pu, Lilin Yi, Chenhao Dai, Weisheng Hu et al.
5 citations
National Science Review
Optical Network Technologies
3.65
article

Experimental demonstration of integrated encryption and communication over optical fiber

Guoqing Pu, Lilin Yi, Chenhao Dai, Weisheng Hu, Zekun Niu, Hang Yang, Yunhao Xie, Minghui Shi, Chuyan Zeng, Guozhi Xu, Lyv Li
article en
5 citations

Abstract

As we enter the big data and artificial intelligence (AI) era, integrating security and communication over optical fiber has become a critical challenge. This urgency is driven by the need to protect vast amounts of sensitive data, ensuring privacy security across global high-capacity optical networks. Traditional secure communication methods often struggle to maintain high-capacity transmission performance while providing robust security. Here we propose an integrated encryption and communication (IEAC) framework, designed to maximize mutual information (MI) for legal users while minimizing it for potential eavesdroppers. Enabled by end-to-end deep learning, this holistic framework trains a random number-selected geometric constellation shaping scheme to optimize encryption processes and transmission quality simultaneously. The IEAC experiment system achieves a groundbreaking single-channel transmission rate of 1 Terabit per second (Tb/s) over a 1200-km fiber link, employing a 26-channel, 3.9 THz bandwidth, full C-band wavelength division multiplexing (WDM) configuration. The MI for eavesdroppers is under 0.2 bit per symbol where the regular value is near 4.0, ensuring secure transmission. The IEAC scheme offers a scalable, promising solution to meet the escalating demand for high-throughput, secure data transmission in the face of advancing big data and AI computational technologies.

National Science ReviewVol. 12(7)
Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China, Shanghai Jiao Tong University
Openalex Percentile: Top 7%
Optical Network Technologies
3.65
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