Breaking the YASS algorithm via pixel and DCT coefficients analysis
Xiaoyi Yu, Noboru Babaguchi · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · 2008
In this paper, we present a steganalytic method that can reliably detect messages hidden in JPEG images using the steganographic algorithm YASS, which is a JPEG steganographic method shown to be undetectable using current best blind steganalysis classifiers. The key element of the method is features extracted from the imagepsilas pixels and DCT coefficients. Although the YASS process effectively disables the calibration based and the noise model based JPEG steganalyzers, it also disturbs the pixels and DCT coefficients dependency after the secret message embedding. An SVM based classifier is trained based on the extracted features for the detection of the presence of steganography. The method is tested on a diverse set of test images that include both originally uncompressed and compressed images in the TIF and JPEG formats. Our experimental results have demonstrated that the proposed steganalyzers can reliably break YASS.