This paper addresses a novel steganography method for images. Most statistical steganalysis algorithms are strong to defeat previous steganography algorithms. RS steganalysis and pixel difference histogram analysis are two well-known statistical steganalysis algorithms which detect non-random changes caused by embedding a secret message into cover image. In this paper, we first explain how two ...

Through dynamic compensation of pixel values of the LSB (Least Significant Bit) embedded image, this paper presents a novel LSB information hiding method against pixels Sample Pairs Steganalysis (SPA), a powerful steganalysis method proposed by Dumitrescu et al. with high precision. This approach embeds messages in the LSB plane of the carrier image randomly via a chaotic system, then makes a d...

The increasing use of steganography requires digital forensic examiners to consider the extraction of hidden information from digital images encountered during investigations. The first step in extraction is to identify the embedding method. Several steganalysis systems have been developed for this purpose, but each system only identifies a subset of the available embedding methods and with var...

In this paper , a steganalysis scheme based on multiple features formed by statistical moments of wavelet characteristic functions is proposed. Our theoretical analysis has pointed out that the defined n-th statistical moment of a wavelet characteristic function is related to the n-th derivative of the corresponding wavelet histogram, and hence is sensitive to data embedding. The selection of t...

This paper deals with the study of interest in the fields of Steganography and Steganalysis. Steganography involves hiding information in a cover media to obtain the stego media in such a way that the cover media is perceived not to have any embedded message for its unintended recipients. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can...

Quantitative steganalysis aims to estimate the amount of payload in a stego object, and such estimators seem to arise naturally in steganalysis of Least Significant Bit (LSB) replacement in digital images. However, as with all steganalysis, the estimators are subject to errors, and their magnitude seems heavily dependent on properties of the cover. In very recent work we have given the first de...

The information-hiding ratio is a well-known metric for evaluating steganalysis performance. In this paper, we introduce a new metric of image complexity to enhance the evaluation of steganalysis performance. In addition, we also present a scheme of steganalysis of least significant bit (LSB) matching steganography, based on feature mining and pattern recognition techniques. Compared to other w...

This paper presents a consolidated view of the computational intelligence used in the natural language steganalysis. In order to understand the human intelligence on natural language, four major computational intelligence methods have been identified. They are bayesian, fuzzy logic, neural network, and genetic algorithm. This paper also presents a measurement tool to measure the natural languag...

In the last few years, we have seen many new and powerful steganography and steganalysis techniques reported in the literature. In the following paper we go over some general concepts and ideas that apply to steganography and steganalysis. Specifically we establish a framework and define notion of security for a steganographic system. We show how conventional definitions do not really adequatel...

This paper examines the effects upon steganalysis classifier performance of introducing superfluous variation into digital cover images . By using fixed steganography and steganalysis tools (Steghide 0.5.1 for former and Stegdetect 0.6 for latter), a number of different image filters are individually applied to cover images prior to the introduction of steganographic content; the effect of thes...