Detection of perturbed quantization (PQ) steganography based on empirical matrix

Perturbed Quantization (PQ) steganography scheme is almost undetectable with the current steganalysis methods. We present a new steganalysis method for detection of this data hiding algorithm. We show that the PQ method distorts the dependencies of DCT coefficient values; especially changes much lower than significant bit planes. For steganalysis of PQ, we propose features extraction from the empirical matrix. The proposed features can be exploited within an empirical matrix of DCT coefficients which some most significant bit planes were deleted. We obtain four empirical matrices and fuse resulted features from these matrices which have been employed for steganalysis. This technique can detect PQ embedding on stego images with 77 percent detection accuracy on mixed embedding rates between 0.05 _ 0.4 bits per non-zero DCT AC coefficients (BPNZC). Comparing the results, we also show that the detection rates are effectively comparable with respect to current steganalysis techniques for PQ steganography.