Image scrambling encryption using chaotic map and genetic algorithm: a hybrid approach for enhanced security

Image encryption plays a crucial role in safeguarding sensitive visual data from unauthorized access. In this research, we propose a novel hybrid approach for image encryption that combines the strength of chaotic maps and the optimization power of Genetic Algorithm (GA). The proposed method aims to enhance encryption security, complexity, and robustness to various attacks. The encryption process begins with the application of a chaotic map, specifically the Sine fusion chaos, to scramble the positions of image pixels. This chaotic map introduces chaos and non-linearity, rendering the image data indiscernible. In the subsequent step, AES and Genetic Algorithm is introduced to encrypt the image. The GA dynamically evolves the encryption process, aiming to find an optimal cipher image that maximizes encryption security and minimizes the possibility of unauthorized decryption. Experimental results demonstrate that the proposed hybrid approach outperforms traditional image encryption methods in terms of resistance to attacks, robustness, and visual obfuscation. This suggested work demonstrated the algorithm’s resilience to statistical attacks by achieving a maximum entropy of 7.99 and almost zero correlation, despite numerous analyses being conducted on the algorithm. The security analysis reveals the strength of our scheme against various cryptographic attacks. The hybrid encryption technique is suitable for applications requiring heightened image security, such as medical imaging, confidential document transfer, and satellite imagery.