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Digital image encryption utilizing high-dimensional cellular neural networks and lower-upper triangular decomposition

Limin Tao¹, Xikun Liang¹, Lidong Han¹

¹School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China.

Science Progress

|September 9, 2025

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This study introduces a novel digital image encryption algorithm using a six-dimensional cellular neural network and chaos theory. The method enhances security and efficiency in image communication by integrating image decomposition and nonlinear transforms.

Area of Science:

Cryptography and Network Security
Applied Mathematics
Computer Science

Background:

Existing image encryption methods face challenges in key space, password generation, security verification, and overall encryption schemes.
There is a need for advanced algorithms to address these limitations in digital image security.

Purpose of the Study:

To develop a novel digital image encryption algorithm addressing current limitations.
To enhance the security, efficiency, and complexity of image cryptosystems.

Main Methods:

Integration of a six-dimensional cellular neural network with generalized chaos for pseudo-random number generation.
Application of Lower-Upper (LU) decomposition to transform the image matrix into L- and U-matrices.
Simultaneous encryption of L- and U-matrices using distinct cipher sequences generated by the integrated chaotic system.

Keywords:

Image encryption LU decomposition cellular neural network non-linear transforms security analysis

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Main Results:

The proposed algorithm successfully generates plaintext-related ciphers.
Image decomposition encryption effectively reduces cipher length and transmission interception risks.
The use of nonlinear transforms significantly enhances cryptosystem complexity and algorithm security.

Conclusions:

The developed algorithm offers a novel image decomposition encryption mode with comprehensive advantages over existing methods.
The algorithm demonstrates strong feasibility and security through simulations and performance analysis.
This approach is promising for future applications in secure image communication.