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

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

A data hiding scheme using parity-bit pixel value differencing and improved rightmost digit replacement

The fundamental objectives of image steganographic algorithm are to simultaneously achieve high payload, good visual imperceptibility, and security. This paper proposes a new data hiding method that increases visual quality and payload, as well as maintains steganographic security. The proposed scheme consists of two novel methods of parity-bit pixel value difference (PBPVD) and improved rightmost digit replacement (iRMDR). It partitions the cover image into two non-overlapping pixel blocks. The difference value between pixels in each block is used to determine the selection of PBPVD and iRMDR. According to the experimental results, the iRMDR method attains the best closest stego-pixels for good visual imperceptibility by resolving the region inconsistency problem in the existing RMDR method. In addition, the method reduces the risk of regular/singular (RS) detection attacks caused by its pixel-digit replacement nature. The PBPVD method exploits the pixel value difference (PVD) to adjust an extra parity bit that increases the payload while retaining the similar visual quality of PVD. Moreover, the iterative readjustment process of PBPVD minimizes the underflow/overflow problem. Overall, the proposed method achieves the steganographic objectives and reduces the detection artifacts against RS and pixel difference histogram analysis

A data hiding scheme using parity-bit pixel value differencing and improved rightmost digit replacement

The fundamental objectives of image steganographic algorithm are to simultaneously achieve high payload, good visual imperceptibility, and security. This paper proposes a new data hiding method that increases visual quality and payload, as well as maintains steganographic security. The proposed scheme consists of two novel methods of parity-bit pixel value difference (PBPVD) and improved rightmost digit replacement (iRMDR). It partitions the cover image into two non-overlapping pixel blocks. The difference value between pixels in each block is used to determine the selection of PBPVD and iRMDR. According to the experimental results, the iRMDR method attains the best closest stego-pixels for good visual imperceptibility by resolving the region inconsistency problem in the existing RMDR method. In addition, the method reduces the risk of regular/singular (RS) detection attacks caused by its pixel-digit replacement nature. The PBPVD method exploits the pixel value difference (PVD) to adjust an extra parity bit that increases the payload while retaining the similar visual quality of PVD. Moreover, the iterative readjustment process of PBPVD minimizes the underflow/overflow problem. Overall, the proposed method achieves the steganographic objectives and reduces the detection artifacts against RS and pixel difference histogram analysis

A comparative study of steganography using watermarking and modifications pixels versus least significant bit

This article presents a steganography proposal based on embedding data expressed in base 10 by directly replacing the pixel values from images red, green blue (RGB) with a novel compression technique based on watermarks. The method considers a manipulation of the object to be embedded through a data compression triple process via LZ77 and base 64, watermark from low-quality images, embedded via discrete wavelet transformation-singular value decomposition (DWT-SVD), message embedded by watermark is recovered with data loss calculated, the watermark image and lost data is compressed again using LZ77 and base 64 to generate the final message. The final message is embedded in portable network graphic (PNG) images taken from the Microsoft common objects in context (COCO), ImageNet and uncompressed color image database (UCID) datasets, through a filtering process pixel of the images, where the selected pixels expressed in base 10, and the final message data is embedded by replacing units’ position of each pixel. In experimentation results an average of 40 dB in peak signal noise to ratio (PSNR) and 0.98 in the similarity structural index metric (SSIM) evaluation were obtained, and evasion steganalysis rates of up to 93% for stego-images, the data embedded average is 3.2 bpp

A High Payload Steganography Mechanism Based on Wavelet Packet Transformation and Neutrosophic Set

In this paper a steganographic method is proposed to improve the capacity of the hidden secret data and to provide an imperceptible stego-image quality. The proposed steganography algorithm is based on the wavelet packet decomposition (WPD) and neutrosophic set. First, an original image is decomposed into wavelet packet coefficients. Second, the generalized parent-child relationships of spatial orientation trees for wavelet packet decomposition are established among the wavelet packet subbands. An edge detector based on the neutrosophic set named (NSED) is then introduced and applied on a number of subbands. This leads to classify each wavelet packet tree into edge/non-edge tree to embed more secret bits into the coefficients in the edge tree than those in the non-edge tree. The embedding is done based on the least significant bit substitution scheme. Experimental results demonstrate that the proposed method achieves higher embedding capacity with better imperceptibility compared to the published steganographic methods