A New Combinational Technique in Image Steganography

A New Combinational Technique in Image Steganography

Sabyasachi Pramanik, Debabrata Samanta, Samir Kumar Bandyopadhyay, Ramkrishna Ghosh
Copyright: © 2021 |Pages: 17
DOI: 10.4018/IJISP.2021070104
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Abstract

Internet is used for exchanging information. Sometimes it is needed to transmit confidential data via internet. Here the authors use image steganography to pass confidential data within a cover image. To construct the algorithm, they take the combinational help of particle swarm optimization (PSO), bi-orthogonal wavelet transform (BWT), and genetic algorithm (GA). They use PSO to take the enhanced version of cover image. They use BWT to choose the selective sub bands of cover image and we utilize GA to select a particular stego image among a set of stego images. Thus, an innovative technique of image steganography has been made to transmit confidential data via cover image generating stego image. This combinational approach of image steganography is quite safe for confidential data transmission and makes it hard for the attackers to retrieve the confidential data.
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In order to determine the optimum coefficients in such transformations, a study was carried out in 2020 (Albalabi, A. and Hamza, N. 2020) regarding applied genetic algorithm (GA) and particle swarm optimization (PSO). In conjunction with a GA and PSO, frequency domain transformations were applied to maximize the performance of a method of image steganography, such as Bandelet Transform and FRIT.

The optimization algorithm is used in research in 2020 (Ansari, A. A. Mohammadi, M. S. and Parvez, M. T. 2020) to figure out optimum coefficients. GA is typically used to choose the best coefficients for transforming the method. Conventional methods based on GA are strongly random, leading to incorrect outcomes. In this sense, an amended GA method to define the optimal coefficients for increasing the integration potential and stego image quality has been suggested. A PSNR value of 50.29 dB is obtained.

The result of the 2019 study (Mohsin A. H. et al. 2019) was used to optimize the selected pixel effectively in the cover image, using a stable and streamlined scheme called the particle swarm optimization. PSO uses the cost-effective fitness function to determine the pixel. Entropy, edge and strength of pixels measured to determine the cost function In addition; the discrete transformation of wavelets is used to achieve robustness and statistical identification. The key goal of the proposed document is to improve protection and to achieve effective PSNR and MSE principles.

A novel system for image steganography was developed in 2020 (Khan, S. et.al. 2020) using the LSB replacement in the contour section of the image. For maximizing data embedding power, the regional value differential was also taken into account. The Artificial Bee Colony Optimization (Neginal, J. and Fatima, R., 2020) Algorithm has been developed to use a new fitness function to determine the best locations for the insertion of data. In contrast with the previous methodology the findings achieved with the proposed approach improve hiding potential by approximately 33%. Therefore an effective PSNR range of 60 to 75 is also obtained.

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