Steganography is the art of covert communication aims at hiding information onto a digital cover media. The choice of the cover medium could be audio, image or video files. Owing to the illegal use of such secret communications, steganalysis the art of code breaking steganography has gained momentum. This paper presents the recent trends in image steganalysis techniques. The two prominent methods have been identified as embedding specific and universal blind steganalysis. As universal blind steganalysis does not demand the prior knowledge of the embedding method, it has become the choice of many steganalysers. It has been identified that universal steganalysis is a two class classification problem and could be implemented with statistical analyses or computational intelligence. As this classification depends on the chosen feature set or the image model, this paper has detailed the feature-based image steganalysis techniques. The curse of dimensionality increased computational time of the chosen feature sets compel the use of statistical feature reduction methods. Hence, the features set optimisation technique have been reviewed in detail.
['J. Anita Christaline', 'R. Ramesh', 'D. Vaishali']
Critical review of image steganalysis techniques