A New Combinational Technique in Image Steganography

2021 ◽  
Vol 15 (3) ◽  
pp. 48-64
Author(s):  
Sabyasachi Pramanik ◽  
Debabrata Samanta ◽  
Samir Kumar Bandyopadhyay ◽  
Ramkrishna Ghosh
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Data Transmission ◽  
Image Steganography ◽  
Cover Image ◽  
Orthogonal Wavelet ◽  
Stego Image ◽  
Swarm Optimization ◽  
Confidential Data ◽  
Orthogonal Wavelet Transform

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.

scholarly journals Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

Open Physics ◽  
2016 ◽  
Vol 14 (1) ◽  
pp. 452-462 ◽  
Author(s):  
Duraisamy Jude Hemanth ◽  
Subramaniyan Umamaheswari ◽  
Daniela Elena Popescu ◽  
Antoanela Naaji
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Frequency Domain ◽  
Particle Swarm ◽  
Optimization Techniques ◽  
Image Steganography ◽  
Secret Data ◽  
Stego Image ◽  
Swarm Optimization ◽  
Transform Coefficients

AbstractImage steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT) and Finite Ridgelet Transform (FRIT) are used in combination with GA and PSO to improve the efficiency of the image steganography system.

scholarly journals A new encrypted method in image steganography

2019 ◽  
Vol 14 (3) ◽  
pp. 1412 ◽  
Author(s):  
Sabyasachi Pramanik ◽  
R P Singh ◽  
Ramkrishna Ghosh
Keyword(s):  
Data Hiding ◽  
Image Steganography ◽  
Cover Image ◽  
Human Response ◽  
Stego Image ◽  
Response Test ◽  
Confidential Data

<p>Steganography is data hiding technique in internet. Here we send CAPTCHA codes within a cover image using Image steganography. CAPTCHA are the crazy codes. They are used in human response test. The word is actually an acronym for: "<strong>C</strong>ompletely <strong>A</strong>utomated <strong>P</strong>ublic <strong>T</strong>uring test to tell <strong>C</strong>omputers and <strong>H</strong>umans <strong>A</strong>part". It is a type of challenge–response test used in computing to determine whether or not the user is a human. Websites implement CAPTCHA codes into their registration processes due to spam. This is the utility of CAPTCHA codes. Here we generate CAPTCHA codes and later send them in an encrypted version. So, actually CAPTCHA codes are embedded into cover image with an encrypted form resulting stego image and thus attackers cannot fetch the actual CAPTCHA resulting in a secured transmission of confidential data using image steganography.</p>

scholarly journals Imperceptible Steganography Scheme with High Payload Capacity using Genetic Algorithm and Particle Swarm Optimization

2019 ◽  
Vol 9 (1) ◽  
pp. 917-923 ◽  
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Data Embedding ◽  
Secret Data ◽  
Swarm Optimization ◽  
High Data ◽  
Confidential Data ◽  
Payload Capacity ◽  
High Payload

Security is the most significant parameter in all type of confidential data transfers. Steganography is used to enhance the security of such confidential communications. Steganography is a method of covert communication in which the existence of secrecy is concealed. In image steganography, achieving high data embedding capacity and simultaneously retaining good visual quality is a very tricky and difficult objective. In this paper, a reversible, secure, extremely imperceptible and high payload capacity steganography technique in the spatial domain is proposed. The proposed method employs evolutionary computation techniques to identify the most optimum locations and arrangements for secret data embedding. The proposed technique uses Particle Swarm Optimization to find the best possible order of data hiding whereas Genetic algorithm is used to identify the best possible arrangements to modify secret data to produce least amount of change in cover-image. The result of the proposed scheme is compared with many steganography techniques and the proposed scheme outperforms the existing schemes in terms of imperceptibility. The proposed technique produces an average PSNR value of 46.40 dB at 2 bit per pixel data embedding rate.

scholarly journals A High-Capacity Image Steganography Method Using Chaotic Particle Swarm Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Aya Jaradat ◽  
Eyad Taqieddin ◽  
Moad Mowafi
Keyword(s):  
Particle Swarm Optimization ◽  
Image Quality ◽  
High Capacity ◽  
Particle Swarm ◽  
Image Steganography ◽  
Embedding Capacity ◽  
Secret Data ◽  
Stego Image ◽  
Swarm Optimization ◽  
Chaotic Particle Swarm Optimization

Image steganography has been widely adopted to protect confidential data. Researchers have been seeking to improve the steganographic techniques in order to increase the embedding capacity while preserving the stego-image quality. In this paper, we propose a steganography method using particle swarm optimization and chaos theory aiming at finding the best pixel locations in the cover image to hide the secret data while maintaining the quality of the resultant stego-image. To enhance the embedding capacity, the host and secret images are divided into blocks and each block stores an appropriate amount of secret bits. Experimental results show that the proposed scheme outperforms existing methods in terms of the PSNR and SSIM image quality metrics.

scholarly journals Hybrid Image Steganography Method Using LZW and Genetic Algorithm for Hiding Confidential Data

2020 ◽  
Author(s):  
Abdulkarem Almawgani ◽  
Adam Alhawari ◽  
Wlaed Alarashi ◽  
Ali Alshwal
Keyword(s):  
Genetic Algorithm ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Message ◽  
Adjustment Process ◽  
Discrete Wavelet ◽  
Secret Data ◽  
Stego Image ◽  
Lzw Algorithm

Abstract Digital images are commonly used in steganography due to the popularity of digital image transfer and exchange through the Internet. However, the tradeoff between managing high capacity of secret data and ensuring high security and quality of stego image is a major challenge. In this paper, a hybrid steganography method based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm, Genetic Algorithm (GA), and the Optimal Pixel Adjustment Process (OPAP) is proposed. The cover image is divided into non-overlapping blocks of nxn pixels. Then, the HDWT is used to increase the robustness of the stego image against attacks. In order to increase the capacity for, and security of, the hidden image, the LZW algorithm is applied on the secret message. After that, the GA is employed to give the encoded and compressed secret message cover image coefficients. The GA is used to find the optimal mapping function for each block in the image. Lastly, the OPAP is applied to reduce the error, i.e., the difference between the cover image blocks and the stego image blocks. This step is a further improvement to the stego image quality. The proposed method was evaluated using four standard images as covers and three types of secret messages. The results demonstrate higher visual quality of the stego image with a large size of embedded secret data than what is generated by already-known techniques. The experimental results show that the information-hiding capacity of the proposed method reached to 50% with high PSNR (52.83 dB). Thus, the herein proposed hybrid image steganography method improves the quality of the stego image over those of the state-of-the-art methods.

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