Blind steganalysis based on classifying feature vectors derived from images is becoming increasingly more powerful. For steganalysis of JPEG images, features derived directly in the embedding domain from DCT coefficients appear to achieve the best performance (e.g., the DCT features and Markov features). The goal of this paper is to construct a new multi-class JPEG steganalyzer with markedly im...

The goal of Forensic Steganalysis is to detect the presence of embedded data and eventually extract the secret message. A necessary step toward extracting the data is determining the steganographic algorithm used to embed the data. In this paper, we construct blind classifiers capable of detecting steganography in JPEG images and assigning stego images to 6 popular JPEG embedding algorithms. Th...

This paper presents a method for detection of double JPEG compression and a maximum likelihood estimator of the primary quality factor. These methods are essential for construction of accurate targeted and blind steganalysis methods for JPEG images. The proposed methods use support vector machine classifiers with feature vectors formed by histograms of low-frequency DCT coefficients. The perfor...

A JPEG image is double-compressed if it underwent JPEG compression twice, each time with a different quantization matrix but with the same 8 × 8 grid. Some popular steganographic algorithms (Jsteg, F5, OutGuess) naturally produce such double-compressed stego images. Because double-compression may significantly change the statistics of DCT coefficients, it negatively influences the accuracy of s...

The goal of forensic steganalysis is to detect the presence of embedded data and to eventually extract the secret message. A necessary step towards extracting the data is determining the steganographic algorithm used to embed the data. In the paper, we construct blind classifiers capable of detecting steganography in JPEG images and assigning stego images to six popular JPEG embedding algorithm...

This paper presents a blind steganalysis technique to effectively attack the JPEG steganographic schemes i.e. Jsteg, F5, Outguess and DWT Based. The proposed method exploits the correlations between block-DCTcoefficients from intra-block and inter-block relation and the statistical moments of characteristic functions of the test image is selected as features. The features are extracted from the...

Our recently introduced JPEG steganographic method called Yet Another Steganographic Scheme (YASS) can resist blind steganalysis by embedding data in the discrete cosine transform (DCT) domain in randomly chosen image blocks. To maximize the embedding rate for a given image and a specified attack channel, the redundancy factor used by the repeat-accumulate (RA) code based error correction frame...

Image steganography is a technique of embedding secret message into a digital image to securely send the information. In contrast, steganalysis focuses on detecting the presence of secret messages hidden by steganography. The modern approach in steganalysis is based on supervised learning where the training set must include the steganographic and natural image features. But if a new method of s...

Steganography is the art of secret communication between two parties that not only conceals the contents of a message, but also its existence. Steganalysis attempts to detect the existence of embedded data in a steganographically altered cover file. Many algorithms have been proposed, but so far each has had some weakness that has allowed its effects to be detected, usually through first or sec...

We present further extensions of yet another steganographic scheme (YASS), a method based on embedding data in randomized locations so as to resist blind steganalysis. YASS is a JPEG steganographic technique that hides data in the discrete cosing transform (DCT) coefficients of randomly chosen image blocks. Continuing to focus on JPEG image steganography, we present, in this paper, a further st...