Steganography and steganalysis are the prominent research fields in information hiding paradigm. This work presents a novel framelet transform based image steganography scheme that hides a secret image into cover image. Perfect reconstruction, sparsity, and stability enables framelet transform to be considered as suitable decomposition technique to obtain transform coefficients. The scheme also benefits from bidiagonal singular value decomposition. Secret information is embedded in singular values of framelet coefficients and stego is obtained. A variety of experiments is conducted to judge the efficacy of proposed method. Simulation results prove that stego images possess better visual quality and are robust to several popular image processing operations. Security performance of proposed method is investigated using various steganalysis schemes that include Gabor filter based, wavelet based and contourlet based steganalysis. Detection accuracy is found to be poor in all cases and confirms the undetectability.

Secure image steganography using framelet transform and bidiagonal SVD

Steganography is a technology which is utilized in securing information through hiding data over another data which can be stored or passed over public network without a clue that secret data is hidden in the cover medium. This article focus on securing and hiding the data through transform domain techniques used in Image, Audio and Video steganography. The review study throws light on the algorithm and properties of transform domain techniques and its benefits to utilize in securing data. Parameters such as imperceptibility, capacity and robustness are evaluated for discrete cosine transform (DCT) and discrete wavelet transform (DWT). Key-words—Steganography; Discrete cosine transform; Discrete Fourier Transform; Discrete Wavelet Transform; Network security; Secure Communication Received: August 26, 2020 . Revised: November 16, 2020. Accepted: January 15, 2021. Published: January 22, 2021.

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Securing Data: A Study on Different Transform Domain Techniques

This paper presents the transform domain image steganography schemes using three popular matrix factorization techniques and contourlet transform. It is known that security of image steganography is mainly evaluated using undetectability of stego image when steganalyzer examines it in order to detect the presence of hidden secret information. Good imperceptibility only suggests eavesdropper’s inability to suspect about the hidden information; however stego image may be analyzed by applying certain statistical checks when it is being transmit- ted through the channel. This work focusses on improving undetectability by employing ma- trix decomposition techniques along with transform domain image steganography. Singular value decomposition (SVD), QR factorization, Nonnegative matrix factorization (NMF) are employed to decompose contourlet coefficients of cover image and secret is embedded into its matrix factorized coefficients. The variety of investigations include the effect of matrix decomposition techniques on major attributes of image steganography like imperceptibility, robustness to a variety of image processing operations, and universal steganalysis perfor- mance. Better imperceptibility, large capacity, and poor detection accuracy compared to existing work validate the efficacy of the proposed image steganography algorithm. Compa- rative analysis amongst three matrix factorization methods is also presented and analyzed.

Image steganography using contourlet transform and matrix decomposition techniques

A high capacity multi-image steganography technique based on golden ratio and non-subsampled contourlet transform

Image steganography is an essential method in the subject of information hiding, which is the art of concealing confidential data within a regular image to prevent tampering. There is a risk of tampering with medical images when they are transmitted over an insecure public network, which makes it difficult for diagnosis. As a result, it's critical to ensure the integrity of these images to avoid any unwanted changes. In this paper, we use the SHA256 technique to calculate the hash value of ROI to ensure medical image integrity. DCT and IDCT will be used to embed the hash in the RONI. We may check the image's authenticity by evaluating the hash value at the receiver end. The hash function does not match if there is any tampering. This study presents a hybrid approach to enhancing security. The altered image is encased in a regular-looking image. It aids in the concealment of confidential data. This multi-pronged approach will improve security.

Enhanced Security In Medical Image Steganography -A Hybrid Approach Using Spatial And Transform Domain

In this paper, a new method for RGB image steganography is being proposed which hides RGB secret image in a RGB cover image by dividing both the secret and cover image in three color planes (red, green, blue) Then among those color planes, the actual color value of an image pixel has been hidden within the same color plane of the cover image using discrete cosine transformation To hide the secret bit, here the desired cover bit can be chosen from a set of 8 bits, which provides better security This proposed technique has been tested using different color images, and experimental results have been analyzed by various quality metrics which assures better imperceptibility

Blind RGB Image Steganography Using Discrete Cosine Transformation

Steganography is a widely-used technique for digital data hiding. Image steganography is the most popular among all other kinds of steganography. In this article, a novel key-based blind method for RGB image steganography where multiple images can be hidden simultaneously is described. The proposed method is based on Discrete Cosine Transformation (DCT) and Discrete Wavelet Transformation (DWT) which provides enhanced security as well as improve the quality of the stego. Here, the cover image has been taken as RGB although the method can be implemented on grayscale images as well. The fundamental concept of visual cryptography has been utilized here in order to increase the capacity to a great extent. To make the method more robust and imperceptible, pseudo-random number sequence and a correlation coefficient have been used for embedding and the extraction of the secrets, respectively. The robustness of the method is tested against steganalysis attacks such as crop, rotate, resize, noise addition, and histogram equalization. The method has been applied on multiple sets of images and the quality of the resultant images have been analyzed through various matrices namely ‘Peak Signal to Noise Ratio,' ‘Structural Similarity index,' ‘Structural Content,' and ‘Maximum Difference.' The results obtained are very promising and have been compared with existing methods to prove its efficiency.

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Multi-Image Hiding Blind Robust RGB Steganography in Transform Domain

The aim of this paper is to establish a new method for RGB image steganography which can hide more than one RGB secret image in a single RGB cover image. To do so, discrete cosine transformation is used here in a block-wise manner. The cover image is divided into three-color channels (Red, Green, and Blue) and each channel is further divided into 8 × 8 blocks. From each block, one bit can be selected to replace with one-pixel value of a secret. Now according to the block size, more than one bit can be manipulated as after applying DCT on a block, mid-band and lower band coefficients have considerably less impact on the overall image. If 3 bits are chosen, then for each block those 3 bits will be replaced by the values from 3 respective secret images. Hence each channels of the cover will contain the same color channel values of the secrets. Just following these steps in reverse order extraction can easily be done and the steganography method will be blind i.e. there will be no need for original cover image while extracting the secrets. Now to enhance the security, before embedding, the secret image is encrypted using Arnold transformation. The proposed method has been thoroughly tested using different color images and the results of these experiments have been scrutinized through various quality metrics, which prove its effectiveness.

Emlon Ghosh

Papers

Blind RGB Image Steganography Using Discrete Cosine Transformation

Multi-Image Hiding Blind Robust RGB Steganography in Transform Domain

Multiple RGB Image Steganography Using Arnold and Discrete Cosine Transformation