Intelligent dynamic data perturbation OCDM encryption scheme based on cellular neural network and biological genetic...

Area of Science:

• Optical Communications
• Information Security
• Signal Processing

Background:

• Existing optical communication systems face challenges in data security and anti-interference capabilities.
• Need for robust encryption methods in high-speed optical networks is growing.
• Orthogonal Chirp Division Multiplexing (OCDM) offers potential for improved system performance.

Purpose of the Study:

• To propose a novel, intelligent dynamic perturbation orthogonal chirp division multiplexing (OCDM) encryption scheme.
• To enhance the security and performance of data transmission in seven-core optical fiber.
• To achieve ultra-high security encryption through multi-dimensional masking and dynamic scrambling.

Main Methods:

• Utilized chaotic sequences from a cellular neural network to generate six masking vectors for six-dimensional encryption.
• Employed DNA operation rules for interleaving bit data and scrambled subcarrier frequency, symbol matrix, and time.
• Implemented dynamic changes in encoding/decoding rules, key base sequence, subcarrier frequency, symbol matrix, and scrambling positions for enhanced robustness.
• Applied OCDM technology to optimize system anti-interference and bit error performance.

Main Results:

• Achieved an ultra-large key space of 10^1170, providing robust security.
• Demonstrated a 70 Gb/s encrypted OCDM signal transmission over a 2 km seven-core fiber.
• OCDM system exhibited 1.2 dB better receiver sensitivity than OFDM at a bit error rate of 10^-3.
• The proposed scheme showed enhanced robustness against malicious attacks.

Conclusions:

• The proposed intelligent dynamic perturbation OCDM encryption scheme offers superior security and performance.
• The scheme significantly improves anti-interference capabilities and bit error rates compared to traditional OFDM.
• This innovative approach holds great promise for securing future optical access networks.