A DNA-Dynamic Permutation-Diffusion Algorithm for Image Encryption Using Scaling Chaotification Models and Advanced DNA Operations

Abstract

The rise in cyber threats to digital images over networks is a primary problem for both private and government organisations. Image encryption is considered a useful way to secure the digital image; however, it faces critical challenges such as weak key generation, chosen-plaintext attacks, high overhead, and scalability. To overcome these challenges, this paper proposes the DNA-Dynamic Concurrent Permutation-Diffusion Algorithm (DNA-DCP-DA), which introduces four advanced encryption mechanisms. Firstly, new scaling chaotification models are introduced to enhance chaotic properties, achieving superior results in bifurcation, Lyapunov Exponent (LE), Sample Entropy (SEn), Kolmogorov Entropy (KEn) and key generation. Secondly, a Key Vectorisation Method (KVM) is proposed to optimise execution time and reduce the computational overhead of chaotic map iterations. Thirdly, robust non-commutative DNA operations are introduced, including DNA hybrid and circular shift operations to enhance encryption security. Finally, integrate permutation and dynamic diffusion processes, strengthening security and improving efficiency. To evaluate the proposed algorithm, extensive experiments have been conducted, and results have been compared with the latest encryption algorithms. This shows the proposed encryption algorithm is better, with superior results for correlation results close to zero and Information Entropy (IE) larger than 7.999. The Number of Pixel Change Rates (NPCR) exceeds 99.6%, and the Uniform Average Change Intensity (UACI) is above 33.4%. The algorithm encrypts an image of size 256 × 256 in 0.1255 s, with a key space reaching 2⁶⁹⁷. As a result, the proposed system establishes a new benchmark for secure and efficient image encryption against cyber threats.