Implementation of 400 Gbps quantum noise stream cipher encryption for 1520 km fiber transmission using end-to-end...

Area of Science:

• Optical Communications
• Cybersecurity
• Quantum Information Science

Background:

• Optical fiber communication networks are vital for large data transmission.
• Physical layer security is crucial for these networks.
• Existing quantum noise stream cipher (QNSC) schemes do not meet the high rates of 400G networks.

Purpose of the Study:

• To enhance the security and rate capabilities of optical fiber communication systems.
• To introduce deep learning into QNSC for improved performance.
• To achieve secure optical communication at rates exceeding current standards.

Main Methods:

• Proposed an end-to-end quantum noise stream cipher (E2E-QNSC) scheme.
• Integrated deep learning into the QNSC framework.
• Utilized 16 quadrature amplitude modulation (QAM) for encryption, resulting in E2E-65536QAM/QNSC.

Main Results:

• Demonstrated secure optical communication at a single-channel rate of 400 Gbps.
• Achieved a total system capacity of 8.4 Tbps.
• Successfully transmitted data over 1520 km with a detection failure probability (DFP) > 0.9999.

Conclusions:

• The E2E-QNSC scheme significantly enhances the security and rate of optical fiber communications.
• The proposed method sets a new record for the rate-distance product in QNSC secure transmission.
• Deep learning integration is a promising approach for advancing physical layer security in high-speed optical networks.