DCT statistics and pixel correlation-based blind image steganalysis for identification of covert communication
by Madhavi B. Desai; S.V. Patel; Vipul H. Mistry
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 9, No. 4, 2020

Abstract: The interconnection of systems through networks, access to information, computer technologies and furtherance of image steganography techniques exploited to send secret information on social network builds the requisite of image steganalysis. Existing image steganalysis methods are either domain specific or the one which requires large dimensional feature set. Considering the types of image steganography methods, embedding rates, image types and feature dimensionality there is an utmost need of a low dimensional blind image steganalysis method. This paper proposes a 32-D DCT statistics and pixel correlation (DSPC) based blind image steganalysis algorithm with the aim to the reduced time complexity of feature extraction as well as the complexity of classifier. The performance of the proposed algorithm is evaluated using experiments with varying embedding message size, message types and image formats using ensemble classifier. The algorithm is implemented in MATLAB and all the experiments are performed on BSDS300 and CorelDraw image datasets.

Online publication date: Fri, 06-Nov-2020

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