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A sector fast encryption algorithm for color images based on one-dimensional composite sinusoidal chaos map.

Ye Tao^1,2,3, Wenhua Cui^1,2,3, Shanshan Wang⁴

¹School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan, China.

|January 24, 2025

Summary

This summary is machine-generated.

This study introduces a novel color image encryption algorithm using one-dimensional composite sinusoidal chaotic mapping (CSCM) for faster and more efficient security in the big data era. The proposed method significantly enhances encryption speed while maintaining robust security against various attacks.

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Area of Science:

Computer Science
Information Security
Applied Mathematics

Background:

Image security is critical for data transmission and storage.
Chaos theory-based image encryption algorithms offer enhanced security.
Existing algorithms face challenges in speed and efficiency for big data.

Purpose of the Study:

To develop a fast color image encryption algorithm for the big data era.
To improve the encryption and decryption speed of color images.
To enhance the overall efficiency and security of image encryption.

Main Methods:

Proposed a one-dimensional composite sinusoidal chaotic mapping (CSCM) by combining basic chaotic maps with sine operations.
Selected and validated the best chaotic mappings (LCS and SCS) using Lyapunov exponent and NIST SP 800-22 tests.
Implemented a parallel encryption process using a fan-shaped diffusion and scrambling technique for improved speed.

Main Results:

Achieved a significantly improved encryption and decryption speed.
Demonstrated a large key space (2^192) and high average information entropy (7.9994).
Exhibited strong security performance with high average NPCR (99.6172) and UACI (33.4646).

Conclusions:

The proposed CSCM-based algorithm offers a substantial improvement in speed and efficiency for color image encryption.
The algorithm provides robust security, effectively resisting common attacks like exhaustion, differential, and noise attacks.
This method is well-suited for securing color images in the big data environment.