Data hiding and extraction using pseudo-random generation and cover image replication

This paper introduces a new algorithm in Steganography for concealing secret messages or images within digital images. The algorithm is designed to produce stego images that can be transmitted to recipients without detection by potential attackers, thereby ensuring secure communication channels. The proposed algorithm employs a multi-level randomization technique to embed data within randomly selected cover images, with each byte of the secret image distributed across multiple cover images. This approach contrasts with conventional methods that hide data within a single cover image. Moreover, the algorithm incorporates a load-balancing priority system, a critical feature that ensures uniform stego image quality across the dataset. This strategic approach minimizes variations in Peak-Signal-to-Noise-Ratio (PSNR) values, contributing to consistent performance during data hiding and extraction processes and enhancing communication security. The security and recoverability of the secret image are further improved by a simplified Cipher key system based on SHA-256, which facilitates pseudo-random number generation. This system ensures that the hidden image can be recovered at the receiver's end, even in the face of potential attacks. Experimental results demonstrate comparable PSNR quality to existing methods, particularly when utilizing equal total resolution to deep hiding algorithms. Notably, the proposed algorithm offers an alternative to encryption by leveraging randomization, thereby complicating data extraction for potential attackers by distributing data across multiple images with a randomly generated cipher key.