Analysis of changes the Renyi divergence for pixel brightness distributions by stego images Wiener filtering

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2018

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Науковий керівник

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Counteraction of sensitive information leakage is topical task today. Special interest is taken to early detection of confidential information unauthorized transmission via commonly used communication systems, such as e-mail, data sharing services, social networks etc. Providing a high detection accuracy of hidden messages (stego files) requires usage of computation intensive detection methods, which are based on cover rich models, usage of artificial neural networks etc. For counteraction to mentioned methods there were proposed detector-aware information embedding, e.g. MG, MiPOD algorithms. These embedding methods allows reducing stegdetector performance (probability of stego file detection) by preserving minimum alterations of cover files, such as digital images. For revealing stego images, formed according to detector-aware embedding methods, there is proposed to analyze differences in results of processing cover and stego images with usage of information-theoretic indices, such as chi-squared divergence, spectrum of Renyi divergence. The paper is devoted to performance analysis of usage the Renyi divergence spectrum for revealing differences between results of cover and stego images Wiener filtering. It is shown that preliminary processing (filtering) of stego images allows amplifying small alterations of cover image caused by information hiding even in case of low cover image payload (less than 10%). It is revealed that usage of Renyi divergence spectrum does not allow significantly improving stego image detection accuracy. Applying of chi-squared divergences allows not only improving detection performance, but also determine type of used steganographic algorithm.

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Progonov, D. Analysis of changes the Renyi divergence for pixel brightness distributions by stego images Wiener filtering / Progonov Dmytro // International Journal “Information Technologies & Knowledge” (IJ ITK). – 2018. – Vol. 12, No. 2. – P. 3-25

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