SVD-based universal spatial domain image steganalysis

Authors:
Gokhan Gul;Fatih Kurugollu
Affiliations:
School of Electronics, Electrical Engineering and Computer Science, Queen's University, Belfast, UK;School of Electronics, Electrical Engineering and Computer Science, Queen's University, Belfast, UK
Venue:
IEEE Transactions on Information Forensics and Security
Year:
2010

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Abstract

This paper is concerned with the universal (blind) image steganalysis problem and introduces a novel method to detect especially spatial domain steganographic methods. The proposed steganalyzer models linear dependencies of image rows/columns in local neighborhoods using singular value decomposition transform and employs content independency provided by a Wiener filtering process. Experimental results show that the novel method has superior performance when compared with its counterparts in terms of spatial domain steganography. Experiments also demonstrate the reasonable ability of the method to detect discrete cosine transform-based steganography as well as the perturbation quantization method.