A Novel Image Steganographic Method based on Integer Wavelet Transformation and Particle Swarm Optimization

Muhuri, Pranab K.; Ashraf, Zubair; Goel, Swati

doi:10.1016/j.asoc.2020.106257

Cited by 62 publications

(31 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, the cover and secret images are divided into four separate blocks. en, for each block, the CPSO algorithm is applied (1) Divide the cover and secret images into blocks using the X-Side-Length and Y-Side-Length particles (2) For each block, convert the secret image into a sequence of bits using the SB-Pole and SB-dire particles (3) if (SB-Pole � 1) (4) Complement the secret bits (5) end if (6) if (SB-dire � 1) (7) Reverse the direction of the secret bits (8) end if (9) Create a sequence of cover pixels using the Direction, X-offset, and Y-offset particles (10) Convert the cover pixels sequence into a sequence of bits using the Bit-Planes and BB-dire particles (11) Apply the CPSO algorithm (Algorithm 1) ( 12) if (number of secret bits < cover pixel bits) (13) Embed secret bits into corresponding cover pixel bits (14) Embed the particles into the last row of cover image (15) Calculate PSNR of the stego-image (16) end if ALGORITHM 2: Pseudocode of data embedding. 6 Security and Communication Networks…”

Section: Resultsmentioning

confidence: 99%

“…Reverse the direction of the secret bits (10) end if (11) Extract the secret pixels from the secret bits (12) Render secret image using the secret pixels (13) end ALGORITHM 3: Pseudocode of data extraction. Security and Communication Networks to find the best pixel locations to embed the secret bits such that the PSNR of the stego-image is maximized.…”

Section: Resultsmentioning

confidence: 99%

“…ese changes lead to the movement of the particles toward the best position in the search area which is known as the best global position (gbest), and each movement of the particle through its favorable position is known as the best particle position (pbest). ese two activities direct the particles to move toward the ideal solution [11]. e new location x t+1 i and velocity v t+1 i of particle i at iteration t + 1 can be expressed as…”

Section: Standard Pso Algorithmmentioning

confidence: 99%

“…pbest i ⟵ x i //Update local best position (11) end if (12) if f(pbest i ) > f(gbest) (13) gbest ⟵ pbest i //Update global best position (14) end if (15) end for (16)…”

Section: Input: Number Of Particles (N) Maximum Iterationsmentioning

confidence: 99%

“…It has been used in various fields, including steganography. For example, in [10,11], PSO was used to find the optimal pixel in the cover image to embed the secret data.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Jaradat

Taqieddin

Mowafi

2021

Security and Communication Networks

View full text Add to dashboard Cite

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.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Standard Pso Algorithmmentioning

confidence: 99%

“…pbest i ⟵ x i //Update local best position (11) end if (12) if f(pbest i ) > f(gbest) (13) gbest ⟵ pbest i //Update global best position (14) end if (15) end for (16)…”

Section: Input: Number Of Particles (N) Maximum Iterationsmentioning

confidence: 99%

“…It has been used in various fields, including steganography. For example, in [10,11], PSO was used to find the optimal pixel in the cover image to embed the secret data.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Jaradat

Taqieddin

Mowafi

2021

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

Advanced reversible stenographic method for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm

2023

Concurrency and Computation

View full text Add to dashboard Cite

SummaryIn this article, an advanced reversible stenographic method is proposed for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm. Here, the cover image and secret message are taken as input. In this image, the edges are identified by Canny edge detection system and embedded by the process of dual‐tree complex wave transformation method (DT‐CWT‐CWOA‐SDH) and pixel edges are optimized using the chaos whale optimization algorithm (CWOA), it optimizes the edge pixel variations and maximizes the robustness of the image and visual quality of stego image. The objective of this process is to increase the security of secret data hiding the secret message on cover image and forming the stego image by the embedding procedure and to maximize the peak signal‐to‐noise ratio (PSNR) and reduce the execution time. The proposed method runs on the MATLAB work site and the performance of proposed method is evaluated using different existing methods. The simulation outcomes illustrate that the proposed DT‐CWT‐CWOA‐SDH shows higher PSNR of 32.01%, 24.79%; lower mean square error (MSE) of 21.13%, 45.185%, normalized correlation (NC) of 11.24%, 19.04% compared with existing method.

show abstract

A survey of recent advances in image steganography

Kumar

Rani

Singh

2022

Security and Privacy

View full text Add to dashboard Cite

Over the course of technological development, data security while transmission and storing has always been a field of continuous advancements and key importance. In the recent times, its importance has increased even further and the main reason behind this is the increase in the amount of data that is being transferred over internet and various networks. Although there are cryptographic approaches to handle these situations, steganography provides a different aspect to the solution. While cryptography encrypts the data such that the cipher text is visible to human eye, but the meaning of that encrypted text is never known. Steganography is the process of hiding data in plain sight inside some images, audio, video and so on, such that it is very difficult for the viewer to directly differentiate if there is some data hidden in the host or not. This paper consists a study of various methodologies to implement Image steganography like spatial domain manipulation, encryption based and deep learning approaches. The paper focuses upon recent advances in all these approaches for image steganography and aims to help other researches in this domain to understand recent developments as well future advancements possible in the same field. Furthermore, this paper illustrates about how different image formats effect various image steganography methods and how the various image color models interact with image steganography. Later this article sheds some light on the domain of steganalysis and reports about the fundamental principles as well as various implementations of steganalysis systems in recent times.

show abstract

A Novel Image Steganographic Method based on Integer Wavelet Transformation and Particle Swarm Optimization

Cited by 62 publications

References 50 publications

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

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

Advanced reversible stenographic method for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm

A survey of recent advances in image steganography

Contact Info

Product

Resources

About