Abstract
This paper proposes a robust optimization of eight chaotic maps: Logistics, Sine, Gauss, Circle, Tent, Chebyshev, Singer, and Piecewise Maps, for superior image encryption. The proposed model consists of two main processes: chaotic confusion and pixel diffusion. In the chaotic confusion process, the positions of the image’s pixels are permuted with the chaotic maps, where the initial condition and the control parameters represent the confusion key. Firstly, the confusion process was performed using the eight chaotic maps without optimization. Then nine metaheuristic optimizers, which are the genetic algorithm, particle swarm optimizations, whale optimization algorithm, dragonfly algorithm, grey wolf optimizer, moth-flame optimizer, sine cosine algorithm, multi-verse optimizer, and ant-lion optimizer, have been used to fine-tune the control parameters of the eight chaotic maps. Then the image’s pixel values are changed using the diffusion function in the pixel diffusion process. Multiple performance metrics, such as entropy, histogram, cross-correlation, computation time analysis, the number of pixels change rate (NPCR), unified average changing intensity (UACI), noise attack, data loss, and key analysis metrics, are utilized to evaluate the proposed model. The results demonstrate that the encryption algorithms based on the eight optimized chaotic maps are more resistant to differential attacks than those without optimization. Furthermore, the optimized Gauss chaotic map is the most computationally efficient, while the chaotic circle map has the most robust key. The careful adjustment of initial conditions and control parameters empowers the chaotic maps to create encryption keys with greater randomness and complexity, thereby increasing the security level of the encryption scheme. Experimental analysis indicates that the correlation coefficient values of images encrypted with the proposed scheme are nearly zero, the histogram of the encrypted images is uniform, the execution time of 0.1556 s, the key space of 10^80, NPCR of 99.63%, UACI of 32.92%, and entropy of 7.997. Moreover, the analysis of noise and cropping attacks, along with the comparison with other algorithms, demonstrate the efficiency and robustness of the proposed algorithm.
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Sameh, S.M., Moustafa, H.ED., AbdelHay, E.H. et al. An effective chaotic maps image encryption based on metaheuristic optimizers. J Supercomput 80, 141–201 (2024). https://doi.org/10.1007/s11227-023-05413-x
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DOI: https://doi.org/10.1007/s11227-023-05413-x