An image steganography using improved hyper-chaotic Henon map and fractal Tromino

Abstract

Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. First, the cover image is converted into a wavelet environment using the integer wavelet transform (IWT), which protects the cover images from false mistakes. The grey wolf optimizer (GWO) is used to choose the pixel’s image that would be utilized to insert the hidden image in the cover image. GWO effectively selects pixels by calculating entropy, pixel intensity, and fitness function using the cover images. Moreover, the secret image was encrypted by utilizing a proposed hyper-chaotic improved Henon map and fractal Tromino. The suggested method increases computational security and efficiency with increased embedding capacity. Following the embedding algorithm of the secret image and the alteration of the cover image, the least significant bit (LSB) is utilized to locate the tempered region and to provide self-recovery characteristics in the digital image. According to the findings, the proposed technique provides a more secure transmission network with lower complexity in terms of peak signal-to-noise ratio (PSNR), normalized cross correlation (NCC), structural similarity index (SSIM), entropy and mean square error (MSE). As compared to the current approaches, the proposed method performed better in terms of PSNR 70.58% Db and SSIM 0.999 respectively.