Analysis of alteration the chi-squared divergence for pixels brightness distributions by cover and stego images filtering


  • D. O. Progonov National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev, Ukraine



digital image, steganalysis, chi-squared divergence


Information protection of government agencies, organizations as well as private corporations is topical task today. Great attention is given to prevention of confidential information leakage by data transmission in global and local communication systems. Revealing and destruction of covert channels require investigation of information flows in communication systems with usage of steganalysis methods. Providing a high detection accuracy (more than 95 %) of formed stego files requires a priory information about features of steganographic methods, used for message embedding into cover files, such as digital images. It leads to significantly decrease the performance of widespread steganalysis in case of stego image formation according to unknown embedding methods. Therefore, it is required a development of universal (blind) stegdetectors, that allow reliable revealing stego images even in case of limited a priory information about used steganographic algorithm. One of the toughest challenges for known universal stegdetectors is revealing of stego images, formed according to advanced adaptive embedding methods. Feature of these methods is minimization of cover image parameters distortions by message hiding. The work is devoted to investigation the effectiveness of preliminary processing (filtering) of cover as well as stego images for improving the accuracy of blind stegdetectors. The case of usage the median and wiener filters for cover/stego image processing is analyzed. Based on the results of research it is revealed that preliminary processing of analyzed images with median and wiener filters gives opportunity to detect weak alterations of cover image’s pixels brightness distributions, caused by stego data embedding according to HUGO and WOW adaptive methods. It is shown that analysis of χ2-divergences between distributions for initial and processed cover as well as stego images allows increasing detection accuracy of universal stegdetectors. Obtained results allow improve stegdetector’s performance even in case of low payload a cover image (less than 10 %), when standard detection methods are inefficient.

Author Biography

D. O. Progonov, National Technical University of Ukraine, Kyiv Politechnic Institute, Kiev

Progonov D. O., Postgraduate student


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Information Security