Abstract
There are currently many obstacles in the way of the design and development of a reliable image steganography system. These include low capacity, weak robustness, and invisibility. Overcoming these restrictions requires enhancing the steganography system’s capacity and security while keeping the signal-to-noise ratio (PSNR) high. Considering these considerations, the purpose of this research is to create a technique to successfully embed secret data into a cover image, thereby realizing a strong steganography scheme. The planning and execution of the suggested method occurred in multiple stages. To boost the scheme’s text security and payload capacity, a novel encryption approach dubbed shuffle the segments of the secret message was integrated with an improved Huffman compression algorithm. To further strengthen the approach, the bit depth of each pixel was doubled from 8 to 12 using a Fibonacci-based picture transformation decomposition method. Third, the schemes were made stealthiest using an enhanced embedding technique that combined a random block or pixel selection with the implicit secret key generation. Experimental evaluations of the suggested scheme’s performance are conducted to determine its stealth, security, robustness, and capacity. Against the proposed scheme, resistance is analyzed for its resistance to non-structural, type 2, and statistical steganography detection attacks. The acquired PSNR values indicated that the proposed technique was successful in achieving higher imperceptibility and security than the reported findings while preserving a larger capacity. In a nutshell, the problems were fixed since the proposed steganography system was superior to existing data hiding schemes on the market.
Keywords
Steganography system; machine learning; deep learning; least significant bit; Fibonacci decomposition