Image Steganography: A Review of the Recent Advances

Abstract

Image Steganography is the process of hiding information which can be text, image or video inside a cover image. The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, which has emerged as a powerful tool in various applications including image steganography, has received increased attention recently. The main goal of this paper is to explore and discuss various deep learning methods available in image steganography field. Deep learning techniques used for image steganography can be broadly divided into three categories -traditional methods, Convolutional Neural Network-based and General Adversarial Network-based methods. Along with the methodology, an elaborate summary on the datasets used, experimental set-ups considered and the evaluation metrics commonly used are described in this paper. A table summarizing all the details are also provided for easy reference. This paper aims to help the fellow researchers by compiling the current trends, challenges and some future direction in this field.

End-to-End Image Steganography Using Deep Convolutional Autoencoders

“…A sender-receiver scheme [36], [37], coverless steganography [38], [39], [3], and cryptography-scheme based [40], [41] are some of the other variations on the implementation of image steganography with GAN model as the base. A detailed description of the recent advances in image steganography can be found in [2].…”

“…Significant Bits (LSB) substitution, Pixel Value Differencing (PVD), Discrete Wavelet Transformation (DWT) were used for hiding the secret information inside a carrier image by exploiting the pixel value of the cover image [2]. However, the hiding capacity of the traditional methods is limited due to embedding capacity issues which can lead to the exposure of the presence of the secret media.…”

Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage

“…Steganography is defined as the science and art of hiding secret information in a way that only the intended recipient can detect the existence of the secret information [ 1 , 2 ]. Secret information is hidden in publicly accessed objects.…”

Increasing the Steganographic Resistance of the LSB Data Hide Algorithm

“…Some steganographic algorithms have become widespread, such as algorithms for applying digital watermarks, which used to embed an image into an image and provide protection against illegal copying or dissemination of information [5]. The most famous and simple steganography algorithms have obvious drawbacks, for example, replacing the color of the hidden message with the background color, such a substitution is easy to notice and reveal the hidden data [6][7]. The book cipher (or its modifications, for example, the book cipher of Aeneas), in which each character of the secret message is replaced by a pointer (for example, the number of a row, column or table), has several significant disadvantages: transmission of small volumes of a secret message; storage and transmission of the key, which can be used to collect a "scattered" message from the so-called stego-container, weak degree of security [8].…”