по
Journal Menu
> Issues > Rubrics > About journal > Authors > About the Journal > Requirements for publication > Council of Editors > List of peer reviewers > Review procedure > Policy of publication. Aims & Scope. > Article retraction > Ethics > Legal information
Journals in science databases
About the Journal

Публикация за 72 часа - теперь это реальность!
При необходимости издательство предоставляет авторам услугу сверхсрочной полноценной публикации. Уже через 72 часа статья появляется в числе опубликованных на сайте издательства с DOI и номерами страниц.
По первому требованию предоставляем все подтверждающие публикацию документы!
MAIN PAGE > Back to contents
Increasing the efficiency of steganoanalysis in the area of discrete wavelet image transformation by analyzing the parameters of the frequency domain of the image
Sivachev Aleksei Vyacheslavovich

graduate student, Department of Design and Safety of Computer Systems, St. Petersburg National Research University of Information Technologies, Mechanics and Optics

197101, Russia, g. Saint Petersburg, Kronverkskii pr., 49

sivachev239@mail.ru

Abstract.

The object of the study are the methods of stegan analysis in the area of discrete wavelet transformation of an image. The author investigate the influence of the fact of embedding in the region of a concrete wavelet transformation on the values of the coefficients of the regions of discrete cosine transform and image in order to improve the efficiency of detecting the fact of embedding into the discrete wavelet transformation domain. The influence of the fact of embedding in the region of discrete wavelet transformation on certain coefficients of regions of discretely cosine transform and discrete sine transformation of the image is shown. The author proposed to use certain coefficients to improve the quality of training of the support vector machine. Method of research: to assess the effectiveness of the steganoanalysis method proposed in the article using the proposed coefficients, a comparison of the efficiency of image classification with other popular steganoanalysis methods for the wavelet decomposition region is performed. As a steganographic influence, the values of the least significant bits of the coefficients of the discrete wavelet transform are used. Main results of the study is the possibility of using certain coefficients of discrete cosine transform and discretely sinus transformation of the region with the purpose of steganoanalysis in the region of discrete wavelet transformation is shown. According to the results of the study, an original method of steganoanalysis is proposed, which makes it possible to increase the efficiency of steganoanalysis for the LH and HL regions of the discrete wavelet transformation of the image. The obtained results can be used in the development of steganoanalysis systems to provide an effective detection of the fact of embedding into the discrete wavelet transformation region of an image.

Keywords: support vector machine, machine learning, discrete sine transform, discrete cosine transform, discrete wavelet transform, frequency domain, steganalysis, steganography, binary classification, wavelet domain

DOI:

10.25136/2306-4196.2018.2.25564

Article was received:

26-02-2018


Review date:

09-03-2018


Publish date:

18-03-2018


This article written in Russian. You can find full text of article in Russian here .

References
1.
Steganography: A Powerful Tool for Terrorists and Corporate Spies [Elektronnyi resurs]/ Stratfor Rezhim dostupa: https://www.stratfor.com/analysis/steganography-powerful-tool-terrorists-and-corporate-spies (Data obrashcheniya 17.07.2016)
2.
An Overview of Steganography for the Computer Forensics Examiner [Elektronnyi resurs]/ Forensic Science Communications-July 2004 Rezhim dostupa: https://www.fbi.gov/about-us/lab/forensic-science-communications/fsc/july2004/research /2004_03_research01.htm (Data obrashcheniya 14.07.2016)
3.
C. Gayathri, V. Kalpana Study on image steganography techniques-International Journal of Engineering and Technology (IJET) Vol 5 No 2 Apr-May 2013 Pages 572-577
4.
Arooj Nissar, A. H. Mir Classification of steganalysis techniques: A study — Digital Signal Processing, Volume 20 Issue 6, December, 2010 Pages 1758-1770
5.
Prokhozhev N.N., Mikhailichenko O.V., Bashmakov D.A., Sivachev A.V., Korobeinikov A.G. Issledovanie effektivnosti primeneniya statisticheskikh algoritmov kolichestvennogo steganoanaliza v zadache detektirovaniya skrytykh kanalov peredachi informatsii // Programmnye sistemy i vychislitel'nye metody-2015.-№ 3.-S. 281-292
6.
Yun Q. Shi, Guorong Xuan, Chengyun Yang, Jianjiong Gao, Zhenping Zhang, Peiqi Chai, Dekun Zou, Chunhua Chen, Wen Chen. Effective steganalysis based on statistical moments of wavelet characteristic function // International Conference on Information Technology: Coding and Computing (ITCC'05). 2005. V. 2. P. 768–773
7.
Konakhovich G.F. Otsenka effektivnosti metodov steganograficheskogo vstraivaniya informatsii v spektral'nuyu oblast' izobrazhenii // Avtomatizirovannye sistemy upravleniya i pribory – 2014.-№168 – S. 59-63
8.
Gireesh Kumar T., Jithin R., Deepa D. Shankar, "Feature Based Steganalysis Using Wavelet Decomposition and Magnitude Statistics", ACE, 2010, Advances in Computer Engineering, International Conference on, Advances in Computer Engineering, International Conference on 2010, pp. 298-300
9.
Farid, Hany, “Detecting Steganographic Messages in Digital Images” Department of Computer Science, Dartmouth College, Hanover NH 03755
10.
Changxin Liu Chunjuan Ouyang Ming Guo Huijuan Chen Image Steganalysis Based on Spatial Domain and DWT Domain Features, Second International Conference on Networks Security Wireless Communications & Trusted Computing (NSWCTC); 2010, p329-331
11.
Sivachev A.V., Prokhozhev N.N., Mikhailichenko O.V., Bashmakov D.A. Effektivnost' steganoanaliza na osnove metodov mashinnogo obucheniya // Nauchno-tekhnicheskii vestnik informatsionnykh tekhnologii, mekhaniki i optiki. 2017. T. 17. № 3. S. 457–466. doi: 10.17586/2226-1494-2017-17-3-457-466
Link to this article

You can simply select and copy link from below text field.


Other our sites:
Official Website of NOTA BENE / Aurora Group s.r.o.
"History Illustrated" Website