Enhanced Multi-Chaotic Fredkin-Logic-Based Image Encryption for Satellite Imagery with Adaptive Hash-Driven Key Generation

Abstract

The secure transmission of satellite imagery is essential for contemporary remote sensing, surveillance, and defense applications. Exchanging large, high-resolution datasets over insecure channels presents significant challenges. Conventional cryptographic algorithms are frequently inefficient for image data because of inherent redundancy and pixel correlations. This study introduces an enhanced encryption framework that combines adaptive hash-driven key generation, multi-chaotic synchronization, and reversible Fredkin logic to achieve both high security and computational efficiency. Dynamic encryption keys are generated using the SHA-256 hash of the input image. Unlike some existing encryption methods that prioritize pixels based on spatial frequency and local contrast features, the proposed framework generates dynamic image-dependent keys using a tri-chaotic system combined with SHA-256 hashing. This approach enhances randomness and key sensitivity while improving resistance to statistical and differential attacks in satellite image encryption.

. Fredkin reversible logic gates facilitate bit-level swapping, ensuring complete reversibility of the encryption process. Reed–Solomon error correction, a coding technique for detecting and correcting data errors, is incorporated into the pipeline to enhance robustness in satellite communication and enable recovery from transmission errors. Experimental results on grayscale images demonstrate that the proposed scheme approaches ideal entropy (7.999), resists differential attacks (with NPCR ≈ 99.6% indicating the percentage of pixels changing between encrypted images after a single pixel change in the original, and UACI ≈ 33.2% measuring the average intensity change), achieves low pixel correlation, and passes all NIST SP 800-22 randomness tests. The framework offers a large key space exceeding 2²⁵⁶ and achieves real-time encryption at 0.19 seconds per frame using GPU-based parallel processing. These results confirm the scheme's security, efficiency, and robustness for real-time satellite image transmission.