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Two-dimensional hyperchaos-based encryption and compression algorithm for agricultural UAV-captured planar images.

Lingzhi Zhou¹, Han Xia¹, Qingfa Lin¹

¹School of Advanced Manufacturing, Guangdong University of Technology, Jieyang, 515200, China.

Scientific Reports

|September 28, 2024

Summary

This summary is machine-generated.

This study introduces a novel 2D-HCFOS system for faster, secure encryption of agricultural drone images. It enhances data security and processing efficiency for unmanned aerial vehicles (UAVs).

Keywords:

Agricultural images Fourier series Image encryption Nonlinear coupled oscillator model Two-dimensional hyperchaos

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Area of Science:

Cybersecurity
Chaos theory
Image processing

Background:

Agricultural unmanned aerial vehicles (UAVs) face slow encryption speeds due to system limitations.
Existing chaotic systems struggle with computational complexity and limited capacity.
Secure transmission of agricultural data is critical for modern farming.

Purpose of the Study:

To develop a high-speed, secure image encryption method for agricultural UAVs.
To overcome the limitations of traditional chaotic encryption systems.
To enhance the robustness and pseudo-randomness of image encryption.

Main Methods:

Integration of compressed sensing with two-dimensional hyperchaotic coupled Fourier oscillator systems (2D-HCFOS).
Utilizing advanced Fourier series and nonlinear coupled oscillators for enhanced security.
Incorporating Bonouille functions in the discrete cosine transform (DCT) domain for a sparser measurement matrix.

Main Results:

The 2D-HCFOS system significantly improves encryption speed and security for agricultural UAV images.
Achieved superior chaotic performance with a Lyapunov index of 15.1039 and sample entropy of 2.4987.
Demonstrated enhanced pseudo-randomness and robustness compared to existing chaotic methods.

Conclusions:

The proposed 2D-HCFOS approach offers a reliable and efficient solution for securing agricultural drone data.
This method enables secure image encryption on personal computers, enhancing UAV operational capabilities.
The study validates the effectiveness and superiority of 2D-HCFOS through rigorous simulations and analysis.