Chaotic Image Encryption by Intra-Channel Diffusion and Inter-Channel Confusion

Most image encryption schemes exhibit one or more of the following limitations: keystream bias, high residual pixel correlation, pattern leakage, low sensitivity to key changes, or a security-efficiency trade-off. We present a robust image encryption framework based on a chaotic system that operates across the red, green, and blue color channels and mitigates all of the above vulnerabilities. The scheme consists of a novel integration of strong bidirectional modular diffusion, inter-channel confusion using a six-state permutation table, and Secure Hash Algorithm 256-based key derivation. Thus, we achieve the following: lossless reconstruction, near-ideal entropy, negligible adjacency correlation, high sensitivity to infinitesimal changes in both the plaintext and the secret key, a complete diffusion effect confirmed by standard differential metrics, and resilience against known- and chosen-plaintext attacks. Furthermore, the results comply with the National Institute of Standards and Technology randomness tests. These results are obtained with competitive encryption times (∼0.37 s for 512 × 512 images) without any code optimization. All of these features make the scheme promising for secure real-time visual data transmission, particularly in telemedicine and Internet of Things surveillance.