Secure Medical Image Steganography Method Based on Pixels Variance Value and Eight Neighbors

The security aspect of processes and methodologies in the information and communication technology era is the main part. The security of information should a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies that are used, and they include steganography, watermark, and cryptography. In cryptography, the secrete message is converted into unintelligible text, but the existence of the secrete message is noticed, on the other hand, watermarking and steganography involve hiding the secrete message in a way that its presence cannot be noticed. Presently, the design and development of an effective image steganography system are facing several challenges such as the low capacity, poor robustness and imperceptibility. To surmount these challenges, a new secure image steganography work called the Pixels Variance (PV) method is proposed along with the eight neighbors method and Huffman coding algorithm to overcome the imperceptibility and capacity issues. In proposed method, a new image partitioning with Henon map is used to increase the security part and has three main stages (preprocessing, embedding, and extracting) each stage has different process. In this method, different standard images were used such as medical images and SIPI-dataset. The experimental result was evaluated with different measurement parameters such as Peak signal-to-noise ratio (PSNR) and Structural Similarity Index (SSIM). In short, the proposed steganography method outperformed the commercially available data hiding schemes, thereby resolved the existing issues.