Institut problem upravleniya imeni V. A. Trapeznikova RAN
Tomskiy gosudarstvennyy universitet sistem upravleniya i radioelektroniki
Russian Federation
Russian Federation
Russian Federation
Tomskiy gosudarstvennyy universitet sistem upravleniya i radioelektroniki
Russian Federation
GRNTI 50.07 Теоретические основы вычислительной техники
BBK 3297 Вычислительная техника
One of the areas of digital image processing is the steganographic embedding of additional information into them. Digital steganography methods are used to ensure the information confidentiality, as well as to track the distribution of digital content on the Internet. Main indicators of the steganographic embedding effectiveness are invisibility to the human eye, characterized by the PSNR metric, and embedding capacity. However, even with full visual stealth of embedding, its presence may produce a distortion of the digital image natural model in the frequency domain. The article presents a new approach to reducing the distortion of the digital image natural model in the field of discrete cosine transform (DCT) when embedding information using the classical QIM method. The results of the experiments show that the proposed approach allows reducing the distortion of the histograms of the distribution of DCT coefficients, and thereby eliminating the unmasking signs of embedding.
information security, steganography, digital images, discrete cosine transform
1. Evsutin O.O. Steganographic embedding of informationinto the frequency domain of the DCT of digital imagesusing the QIM method with variable quantization step /O.O. Evsutin, A.S. Kokurina, R.V. Meshcheryakov //Proceedings of the 28th International Conference onComputer Graphics and Vision «GraphiCon 2018». - 2018.- Russia, Tomsk. - 297-300.
2. Denemark T. Steganalysis Features for Content-AdaptiveJPEG Steganography / T. Denemark, M. Boroumand, J.Fridrich // IEEE Transactions on Information Forensics andSecurity. - 2016. - Vol. 11(8). - P. 1736-1746.
3. Evsutin O. The adaptive algorithm of informationunmistakable embedding into digital images based on thediscrete Fourier transformation / O. Evsutin, A. Kokurina,R. Meshcheryakov, O. Shumskaya // Multimedia Tools andApplications. - 2018. - Vol. 77(21). - P. 28567-28599.
4. Fridrich J. Feature-Based Steganalysis for JPEG Images andits Implications for Future Design of SteganographicSchemes // Lecture Notes in Computer Science. - 2004. -Vol. 3200. - P. 67-81.
5. Holub V. Universal Distortion Function for Steganographyin an Arbitrary Domain / V. Holub, J. Fridrich, T. Denemark// EURASIP Journal on Information Security. - 2014. - №1. - P. 1-13.
6. Kodovsky J. Ensemble Classifiers for Steganalysis ofDigital Media / J. Kodovsky, J. Fridrich, V. Holub // IEEETransactions on Information Forensics and Security. -2012. - Vol. 7(2). - P. 432-444.
7. Mitekin V. A new QIM-based watermarking algorithmrobust against multi-image histogram attack / V. Mitekin,V. Fedoseev // Procedia Engineering. - 2017. - Vol. 201. -P. 453-462.
8. Sedighi V. Content-Adaptive Steganography byMinimizing Statistical Detectability // V. Sedighi, R.Cogranne, J. Fridrich // IEEE Transactions on InformationForensics and Security. - 2016. -Vol. 11(2). - P. 221-234.
