New methodology for breaking steganographic techniques for JPEGs

In this paper, we present general methodology for developing attacks on steganographic systems for the JPEG image format. The detection first starts by decompressing the JPEG stego image, geometrically distorting it (e.g., by cropping), and recompressing. Because the geometrical distortion breaks the quantized structure of DCT coefficients during recompression, the distorted/recompressed image will have many macroscopic statistics approximately equal to those of the cover image. We choose such macroscopic statistic S that also predictably changes with the embedded message length. By doing so, we estimate the unknown message length by comparing the values of S for the stego image and the cropped/recompressed stego image. The details of this detection methodology are explained on the F5 algorithm and OutGuess. The accuracy of the message length estimate is demonstrated on test images for both algorithms. Finally, we identify two limitations of the proposed approach and show how they can be overcome to obtain accurate detection in every case. The paper is closed with outlining a condition that must be satisfied by all secure high-capacity steganographic algorithms for JPEGs

Steganalysis Based on JPEG Compatibility

In this paper, we introduce a new forensic tool that can reliably detect modifications in digital images, such as distortion due to steganography and watermarking, in images that were originally stored in the JPEG format. The JPEG compression leaves unique fingerprints and serves as a “fragile watermark ” enabling us to detect changes as small as modifying the LSB of one randomly chosen pixel. The detection of changes is based on investigating the compatibility of 8×8 blocks of pixels with JPEG compression with a given quantization matrix. The proposed steganalytic method is applicable to virtually all steganographic and watermarking algorithms with the exception of those that embed message bits into the quantized JPEG DCT coefficients. The method can also be used to estimate the size of the secret message and identify the pixels that carry message bits. As a consequence of our steganalysis, we strongly recommend avoiding using images that have been originally stored in the JPEG format as cover-images for spatial-domain steganography

Handling Uneven Embedding Capacity in Binary Images: A Revisit

Hiding data in binary images can facilitate the authentication and annotation of important document images in digital domain. A representative approach is to first identify pixels whose binary color can be flipped without introducing noticeable artifacts, and then embed one bit in each non-overlapping block by adjusting the flippable pixel values to obtain the desired block parity. The distribution of these flippable pixels is highly uneven across the image, which is handled by random shuffling in the literature. In this paper, we revisit the problem of data embedding for binary images and investigate the incorporation of a most recent steganography framework known as the wet paper coding to improve the embedding capacity. The wet paper codes naturally handle the uneven embedding capacity through randomized projections. In contrast to the previous approach, where only a small portion of the flippable pixels are actually utilized in the embedding, the wet paper codes allow for a high utilization of pixels that have high flippability score for embedding, thus giving a significantly improved embedding capacity than the previous approach. The performance of the proposed technique is demonstrated on several representative images. We also analyze the perceptual impact and capacity-robustness relation of the new approach