Steganalysis for clustering modification directions steganography
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In recent time, most of the steganographic methods minimize the embedding cost while maximizing the embedding capacity by injecting message bits in the highly textured regions of the image. Recently, the Clustering Modification Direction (CMD) steganography has been proposed as a wrapper over the additive steganography algorithms, resulting in a substantial improvement in statistical imperceptibility against state-of-the-art steganalytic classifiers. In this paper, a steganalysis scheme, named Selective-Signal-Removal (SSR) is proposed to mount an attack on the CMD algorithm. It has been observed experimentally that the CMD scheme has a tendency to embed in a localized cluster having higher texture. The proposed scheme exploits this fact and tries to predict the embedding zones. It essentially discards the irrelevant region of the image (which may not be modified by the CMD algorithm while embedding) by using a heuristic function with an assignment algorithm to improve the steganalytic detection rate. The experimental results show that the proposed SSR scheme can detect CMD based steganography with improved accuracy.
KeywordsSteganalysis Spatial domain steganalysis CMD steganography
Authors would like to thank the anonymous reviewers for their insightful comments and suggestions. Authors would also like to acknowledge the funding agency, Ministry of Human Resource Development, Government of India.
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