Detection of Perturbed Quantization (PQ) Steganography Based on Empirical Matrix

Perturbed quantization (pq) steganography scheme is almost undetectable with the current steg analysis methods. we present a new steg analysis methodfor detection of this data hiding algorithm. we show that the pq method distorts the dependencies of dct coeffcient values; especially changes much lower than signicant bitplanes. for steg analysis of pq, we propose features extraction from the empirical matrix. the proposed features can be exploited within an empirical matrix of dct coeffcients which some most signicantbit 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-zerodct ac coeffcients (bpnzc). comparing the results, we also show that the detection rates are effectively comparable with respect to current steganalysis techniques for pq steganography.