MATLAB Code for Image Encryption

Application Background

Image encryption constitutes a vital research field where traditional data encryption techniques prove insufficient due to unique image characteristics including spatial correlation and substantial data volume. Though limited algorithms have been developed, several demonstrate robust performance under specific parameter configurations. Currently, multiple chaos mapping implementation algorithms have been proposed and applied in image encryption, typically implemented through MATLAB functions like logisticMap() or chenSystem() for generating pseudo-random sequences. These algorithms provide strong guarantees for image confidentiality and integrity through pixel permutation and diffusion operations. Additionally, matrix-based encryption methods utilizing MATLAB's matrix manipulation functions (reshape(), inv()) and mathematical principles like modular arithmetic are widely employed in image encryption systems.

Key Technologies

Encryption: Image encryption technology protects visual information security through transformation algorithms that render original images inaccessible to unauthorized users. Typical MATLAB implementations involve XOR operations with chaos sequences or AES adaptations using aesencrypt() custom functions.

Image Encryption: This specialized technique safeguards images by transforming pixel values through substitution-permutation networks, often implemented via MATLAB's imread()/imwrite() functions combined with chaos-based key generation algorithms.

Data Encryption: General data protection technology that secures information through cryptographic processing, with MATLAB implementations frequently using crypt() functions or custom Feistel network structures.

Matrix: A fundamental mathematical concept organized in rows and columns, extensively utilized in MATLAB for representing multidimensional image data through im2double() conversions and performing transformations via matrix multiplication operations.

Mathematics: The discipline studying quantity, structure, and space, providing theoretical foundations for encryption algorithm design in MATLAB, including modular arithmetic operations (mod()) and discrete cosine transforms (dct2()) for frequency-domain encryption.

The above introduction covers application backgrounds for image encryption, providing technical insights for implementation approaches using MATLAB's computational capabilities.