Linguistic response surface methodology approach to measure the quality of nonlinear frame‐pixel and bit place‐based video steganography

Abstract

Steganography refers to the practice of hiding sensitive information inside seemingly unrelated data sets. Steganography in the video is one of the best methods available for hiding data without compromising the film's appearance. For improved security and compatibility, the traditional system uses different video steganography techniques with linear or precise positions. Traditional linear video steganography practices face vulnerability, a lack of security, limited embedding options, and inadequate compatibility. Here nonlinear frame(s) and pixel positions based information hiding techniques have been developed to overwhelm the following. Both the nonlinear frame positions and nonlinear pixel positions are selected for the video‐based steganography. In the beginning, the nonlinear frame positions are selected through the key and the key may be with any prescribed range and alphanumeric characters. A single or more frames may be selected through the key and that entirely depends upon the corresponding run‐through. Then the nonlinear pixel and bit positions are also selected through a similar key. The proposed method is also compared with some former techniques and gives a magnificent result. Furthermore, a security analysis of the suggested algorithm has also been conducted using the differential attack method. To validate the suggested method and ensure that it is accurate, the author of this article made use of a very specific and innovative methodology known as the linguistic response surface methodology (LRSM). This model is framed based on achieving a few steganography assessment measures like PSNR, SSIM, and MSE metric values after incorporating hidden text in various nonlinear frames' nonlinear pixel locations of the video. The analysis of the variance using LRSM for PSNR, SSIM, and MSE response reveals very substantial results with confirmation.