Low-Complexity Features for JPEG Steganalysis Using Undecimated DCT

Abstract

This paper introduces a novel feature set for steganalysis of JPEG images. The features are engineered as first-order statistics of quantized noise residuals obtained from the decompressed JPEG image using 64 kernels of the discrete cosine transform (DCT) (the so-called undecimated DCT). This approach can be interpreted as a projection model in the JPEG domain, forming thus a counterpart to the projection spatial rich model. The most appealing aspect of this proposed steganalysis feature set is its low computational complexity, lower dimensionality in comparison with other rich models, and a competitive performance with respect to previously proposed JPEG domain steganalysis features.