Steganalysis Method for Detecting Embedded Coefficients of Discrete-Wavelet Image Transformation into High-Frequency Domains

  • Alexey V. SivachevEmail author
  • Daniil A. Bashmakov
  • Olga V. Mikhailishenko
  • Anatoliy G. Korobeynikov
  • Roland Rieke
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 971)


The paper deals with a research aimed at providing the highest performance of detection of an embedding into a wavelet-domain image, in particular in LH and HL subbands, due to the combined use of several methods proposed by the authors. The paper discusses various methods for enhancing detection of the embedding into a wavelet-domain image as proposed by the authors for their possible combined use in order to ensure the best possible performance of detecting the embedding into a wavelet-domain image. These methods use the features of the wavelet’s transform, interrelations of various domains of the coefficients obtained by the wavelet transform of the image, or peculiar features or frequency domain of images. By the results of this research, a steganalysis method is proposed, based on the combined use of the above-described methods for increasing the steganalysis efficiency, which allows providing a better performance of detection of a wavelet-domain image embedding compared with existing methods of the steganalysis. The proposed methods of increasing the efficiency of steganalysis will improve the effectiveness of the steganalysis of information embedded in the LH and HL subbands by 4–7% in comparison with the already existing methods. The proposed method is based on combining them and allows you to get an additional increase in efficiency by 1–3%. The results of the given research can be useful for the experts, dealing with the information security problems while detecting and counteracting with the hidden data channel, based on the use of steganography, including in the mobile Internet. The obtained results can be used in the development of steganalysis systems.


Steganography Stego image Steganalysis Binary classification The Haar wavelet Discrete wavelet transform (DWT) Image frequency domain Discrete cosine transformation (DCT) Discrete sine transformation (DST) 



This work was supported by Government of Russian Federation (Grant 08-08).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)St. PetersburgRussia
  2. 2.Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation of the Russian Academy of Sciences St.-Petersburg FilialSt. PetersburgRussia
  3. 3.Fraunhofer-Institute for Secure Information Technology SITDarmstadtGermany

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