JPEG-Compatibility Steganalysis Using Block-Histogram of Recompression Artifacts
Jan Kodovský and Jessica Fridrich (SUNY Binghamton)
JPEG-compatibility steganalysis detects the presence of embedding changes using the fact that the stego image was previously JPEG compressed. Following the previous art, we work with the difference between the stego image and an estimate of the cover image obtained by recompression with a JPEG quantization table estimated from the stego image. To better distinguish recompression artifacts from embedding changes, the difference image is represented using a feature vector in the form of a histogram of the number of mismatched pixels in 8 × 8 blocks. Three types of classifiers are built to assess the detection accuracy and compare the performance to prior art: a clairvoyant detector trained for a fixed embedding change rate, a Neyman–Pearson detector for an unknown change rate, and a quantitative detector. The proposed approach offers significantly more accurate detection across a wide range of quality factors and embedding operations, especially for very small change rates. The technique requires an accurate estimate of the JPEG compression parameters.