Steganalytic features for JPEG compression-based perturbed quantization

Abstract

Perturbed quantization (PQ) data hiding is almost undetectable with the current steganalysis methods. We briefly describe PQ and propose singular value decomposition (SVD)-based features for the steganalysis of JPEG-based PQ data hiding in images. We show that JPEG-based PQ data hiding distorts linear dependencies of rows/columns of pixel values, and proposed features can be exploited within a simple classifier for the steganalysis of PQ. The proposed steganalyzer detects PQ embedding on relatively smooth stego images with 70% detection accuracy on average for different embedding rates.