ABSTRACT With the rapid growth of digital multimedia transmission over open networks, ensuring the security and privacy of digital images is critical. Although conventional encryption methods are effective, they can be vulnerable to differential, brute-force, and cryptanalytic attacks, particularly when applied to high-resolution images. To address these challenges, this work proposes a memristor-based image encryption system that combines chaotic mapping with an enhanced metaheuristic optimization algorithm, the Revamped Gorilla Troop Optimizer (RGTO). The integration of memristor-based chaos with RGTO enables the generation of highly sensitive and unpredictable encryption keys, thereby providing a large key space and strong diffusion property. The proposed approach employs a single-pass encryption framework, making it computationally efficient and suitable for real-time applications, such as video conferencing. Extensive experiments were conducted on standard and high-resolution real-time images to evaluate key performance metrics, including NPCR, UACI, entropy, PSNR, and correlation. The results demonstrate that the proposed method achieves an NPCR of 99.56% and UACI of 33.80%, with an entropy approaching 7.9966, confirming high randomness and resistance against differential attacks. The PSNR values indicate that the decrypted images maintain an acceptable visual quality, whereas the statistical and convergence analyses validate their stability and reliability. Comparative studies with recent state-of-the-art chaotic and metaheuristic encryption methods show that the proposed system provides superior security, better key sensitivity, and higher computational efficiency than the existing methods. These findings confirm that the memristor-based RGTO encryption framework is a robust and practical solution for secure image transmission, ensuring the high-level protection of multimedia data in modern communication networks.
B et al. (Mon,) studied this question.