A novel image encryption scheme based on a 3D enhanced chaotic map and DNA computing model

With the increasing importance of information sharing and storage, image encryption has become a critical method to ensure the confidentiality and integrity of sensitive image data. In this paper, a novel symmetric image encryption algorithm is presented by combining DNA encoding and a proposed three-dimensional enhanced logistic-fraction-sine (3D-ELFS) hyper-chaotic system. The performance of 3D-ELFS is verified through rigorous tests, such as bifurcation diagrams, Lyapunov exponent, permutation entropy, and 0-1 test. In addition, a DNA computing model based on the self-inverting function is proposed, the 8 encoding rules and 7 designed operations are determined by chaotic sequences generated with 3D-ELFS. In addition, the operation number of DNA diffusion is controlled with number of diffusion (ND) factors. After DNA level permutation and diffusion, the ciphertext image is obtained. Through correlation analysis, histogram analysis, information entropy, as well as analysis of metric values such as NPCR, UACI and MSE, it is proven that the proposed encryption algorithm exhibits robustness and security against different attack methods. Experimental results demonstrate the algorithm has high security and usability in practical application scenarios.