Pixel value differencing steganography techniques: Analysis and open challenge

Steganography is the science of secret data communication using carrier medium, such as images, videos, text, and networks. Image steganography is majorly divided into spatial and frequency domains. Pixel value differencing (PVD) considered as good steganographic algorithm due to its high payload and good visual perception in spatial domain. The purpose of this paper is two folded. First is the critical analysis of current PVD methods using evaluating parameters (payload, visual quality and resistance of attacks) and secondly it highlights the current promising directions on PVD steganographic research

Detecting covert communication channels in raster images

Digital image steganography is a method for hiding secret messages within everyday Internet communication channels. Such covert communications provide protection for communications and exploit the opportunities available in digital media. Digital image steganography makes the nature and content of a message invisible to other users by taking ordinary internet artefacts and using them as cover objects for the messages. In this paper we demonstrate the capability with raster image files and discuss the challenges of detecting such covert communications. The contribution of the research is community awareness of covert communication capability in digital media and the motivation for including such checks in any investigatory analysis

A Steganographic Method Based on Pixel-Value Differencing and the Perfect Square Number

The pixel-value differencing (PVD) scheme uses the difference value between two consecutive pixels in a block to determine how many secret bits should be embedded. There are two types of the quantization range table in Wu and Tasi's method. The first was based on selecting the range widths of [8, 8, 16, 32, 64, 128], to provide large capacity. The second was based on selecting the range widths of [2, 2, 4, 4, 4, 8, 8, 16, 16, 32, 32, 64, 64], to provide high imperceptibility. Most of the related studies focus on increasing the capacity using LSB and the readjustment process, so their approach is too conformable to the LSB approach. There are very few studies focusing on the range table design. Besides, it is intuitive to design it by using the width of the power of two. This work designs a new quantization range table based on the perfect square number to decide the payload by the difference value between the consecutive pixels. Our research provides a new viewpoint that if we choose the proper width for each range and use the proposed method, we can obtain better image quantity and higher capacity. In addition, we offer a theoretical analysis to show our method is well defined. The experiment results also show the proposed scheme has better image quantity and higher capacity

Robust Digital Image Steganography Within Coefficient Difference On Integer Haar Wavelet Transform

The development of digital information has lead to increasing demands on information security technology in order to protect the confidentiality of information. Digital steganography is one of technologies that is capable of protecting the information from unauthorized interception. It is due to its capability to hide the embedded of the information without attracting the eavesdropper’s attention. Among digital media, digital image is the most widely used medium for steganography. Discrete Cosine Transform (DCT) is a well known technique in digital image steganography. The use of DCT on small blocks may pose blocking effects and unintended artifacts on the overall image. These disadvantages of DCT can be eliminated by using Discrete Wavelet Transform (DWT) which is more compatible with the Human Visual System (HVS). However the floating point of DWT can causes some loss of information. On the other hand, Integer Wavelet Transform (IWT) represented in finite precision can avoid the problem of floating point precision in DWT. In this paper, the messages are embedded on the 1-level Integer Haar Wavelet Transform (IHWT) using coefficient difference scheme that is adopted from Pixel Value Differencing (PVD). The messages are embedded on the difference values of two adjacent wavelet coefficients. The result shows that the proposed method can easily outperform the existing method that employ IHWT and Pixel Mapping Method (PMM) in term of imperceptibility as well as the maximum capacity