Steganography is the technique for hiding secret information in other data such as still, multimedia images, text, audio. Whereas Steganalysis is the reverse technique in which detection of the secret information is done in the stego image. Steganalysis can be classified on the basis of the techniques used classified statistical techniques, pattern classification techniques and visual detection...

Blind quantitative steganalysis is about revealing more details about hidden information without any prior knowledge of steganograghy. Machine learning can be used to estimate some properties of hidden message for blind quantitative steganalysis. We propose a quantitative steganalysis method based on fusion of different steganalysis features and the estimator relies on gradient boosting. Experi...

Steganography is the art of hiding the secret message in a cover medium and the media could be a audio or video or image. Steganography aims at hiding data as stealthy as possible in a cover medium, Steganalysis aims to detect the presence of any hidden information in the stego media here it refers to the JPEG images. Current Steganalysis aims to focus more on detecting statistical anomalies in...

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...

Steganography is a science of hiding messages into multimedia documents. A message can be hidden in a document only if the content of a document has high redundancy. Although the embedded message changes the characteristics and nature of the document, it is required that these changes are difficult to be identified by an unsuspecting user. On the other hand, steganalysis develops theories, meth...

A mathematical approach to steganalysis is presented in this paper with linear steganography being the main focus. A mathematically formal definition of steganalysis is given followed by definitions for passive and active steganalysis. The steganalysis problem is formulated as blind system identification and conditions for identifiability (successful steganalysis) are derived. A procedure to sy...

In this paper, a general blind steganalysis system is proposed, in which the statistical moments of characteristic functions of the prediction-error image, the test image, and their wavelet subbands are selected as features. Artificial neural network is utilized as the classifier. The performance of the proposed steganalysis system is significantly superior to the prior arts.

YASS is a steganographic algorithm for digital images that hides messages robustly in a key-dependent transform domain so that the stego image can be subsequently compressed and distributed as JPEG. Given the fact that state-of-the-art blind steganalysis methods of 2007, when YASS was proposed, were unable to reliably detect YASS, in this paper we steganalyze YASS using several recently propose...