In this paper, we present a data hiding detection (steganalysis) method based on Zernike moments of discrete wavelet coefficients of an image and SVM. We use Zernike moments of DWT subbands coefficients of an images as features for steganalysis and use support vector machines (SVM) for classification of stego and non-stego images. Experimental results show that there are different between these...

Up to now, most researches on steganalysis concentrate on one extreme case. Typically, the a priori knowledge of the embedding way and cover-media is assumed known in the classifier training and even feature design stage. However, the steganalysis in the real world is done with different levels of such knowledge so that there can be various paradigms for doing it. Although some researchers have...

In the history of human communication, the concept and need for secrecy between the parties has always been present. One way of achieving it is to modify the message so that it is readable only by the receiver, as in cryptography for example. Hiding the message in an innocuous medium is another, called steganography. And the counterpart to steganography, that is, discovering whether a message i...

One of the biggest challenges in universal steganalysis is the identification of reliable features that can be used to detect stego images. In this paper, we present a steganalysis method using features calculated from a measure that is invariant for cover images and is altered for stego images. We derive this measure, which is the ratio of any two Fourier coefficients of the distribution of th...

The objective of steganography is to conceal the presence of a secret communication. Nevertheless, with the development of steganalytic attack, also known as steganalysis, there are many statistical methods to estimate the presence and ratio of secret messages. The chi square (χ 2 ) attack and regular-singular (RS) attack are two well recognized and widely applied statistical steganalysis schem...

This paper proposes a steganalysis technique for both grayscale and color images. It uses the feature vectors derived from gray level co-occurrence matrix (GLCM) in spatial domain, which is sensitive to data embedding process. This GLCM matrix is derived from an image. Several combinations of diagonal elements of GLCM are considered as features. There is difference between the features of stego...

This paper describes a new steganography algorithm based on a steerable pyramid transform of a digital image and the steganalysis of the existence of secret messages hidden by this new method. The data embedding process uses the elements of a Lee and Chen steganography algorithm which is adapted to the steerable pyramid transform domain. This article describes the Fisher Linear Disriminant (FLD...

For the LSB steganography, a fusion method is proposed to fuse two typical quantitative steganalysis methods based on support vector regression (SVR). This paper first gives some main factors influencing the errors of structural steganalysis and weighted stego image steganalysis, viz. the local variance and saturation. Then, the estimated embedding ratios of above two methods, the local varianc...

Steganography and steganalysis are important topics in information hiding. Steganography refers to the technology of hiding data into digital media without drawing any suspicion, while steganalysis is the art of detecting the presence of steganography. This paper provides a survey on steganography and steganalysis for digital images, mainly covering the fundamental concepts, the progress of ste...