Steganalysis method efficient for the hidden communication channel with low capacity
DOI:
https://doi.org/10.30837/rt.2019.3.198.02Keywords:
steganalysis method, digital image, low capacity of the hidden communication channel, singular numbers, singular number gap, the Least Significant Bit methodAbstract
The Least Significant Bit (the LSB-method) remains one of the main steganalysis methods used nowadays for the hidden communication channel organization. One of the features of the current use of the LSB method is an organizing of the hidden communication channel with low capacity. Under such conditions, the vast majority of existing steganalysis methods is ineffective. This paper is dedicated to the development of a new steganalysis method for detection of additional information in digital images embedded by the least significant bit modification. The method is based on the perturbation theory and matrix analysis and effective under the low capacity of the hidden communication channel. This method is based on the analysis of the normalized gap of maximum singular numbers for non-intersecting blocks of an image matrix, obtained by its standard splitting. It is shown that conversion of a digital image from the lossless format to the lossy format with different quality factors will lead to a monotonous increase in the number of blocks for which the normalized gap of block’s maximum singular number increases with a decrease in the quality factor used in compression of the source image. This monotony will be broken in the case when the image originally stored in lossy format is being re-stored in lossy format. The conclusion made is the basis for the developed steganalysis method and the algorithm that implements it, which has polynomial complexity of degree 2. The proposed algorithm exceeds in efficiency the existing analogues when the embedding rate is less then 0.1 bits per pixel and effective for color and grayscale images. The conclusions are confirmed by the given results of a computational experiment, which have involved more than 5,000 digital images.References
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