Stegananalysis of digital images in conditions of varying degrees of contents fullness
DOI:
https://doi.org/10.30837/rt.2018.4.195.16Keywords:
steganalysis, digital image, sequential triads of triplets, spatial domain, losses format, lossless formatAbstract
An improvement of the steganalytic method for detection of the presence of additional information in color digital images which showed high efficiency in identifying stego formed by embedding of secret data only into one color component of the container is presented. The proposed method analyses digital image in the spatial domain and is based on the accounting of sequential color triads in the matrix of unique colors of the digital content. However, in the process of steganographic transformation cases of embedding of confidential data into two and three color components of images are possible that ensures the concealment of a larger amount of information and requires the improvement of the existing method of steganalysis. In the course of the conducted research the character of perturbations in the quantity of sequential triads of triplets in a matrix of unique colors as a result of embedding of additional information into two and three color components of images originally stored in a losses format was analyzed. Considering obtained results the parameters of the original method for detecting of stego was refined. It has been established that the character of changes in the quantity of sequential triads of triplets as a result of steganographic transformation is different in cases of using containers in a losses format and containers in a lossless format. Based on the obtained data the steganalytic method has been improved by integrating it with the method of detection the fact of compression of digital content developed earlier. The developed method provides high efficiency in detecting stego formed with different degree of container fullness without reducing the accuracy of identifying the filled color components if the additional information was embedded into only one color component of the digital images. This method can be used as a basis for complex steganalysis of digital contents by using existing methods that analyzes color matrixes of images separately.References
Стеганография, цифровые водяные знаки и стеганоанализ / А.В. Аграновский, А.В. Балакин, В.Г. Грибунин, С.А. Сапожников. – Москва : Вузовская книга, 2009. – 220 с.
Bohme R. Advanced statistical steganalysis. – Springer, 2010. – 302 p.
Jean-Francois Couchot. Improving Blind Steganalysis in Spatial Domain using a Criterion to Choose the Appropriate Steganalyzer between CNN and SRM+EC / Jean-Francois Couchot, Raphael Couturier, Michel Salomon // ICT Systems Security and Privacy Protection. 32nd IFIP TC 11 International Conference, SEC 2017, Rome, Italy, May 29-31, 2017. – Pp. 327-340. DOI: https://doi.org/10.1007/978-3-319-58469-0_22
Wei Huang. Novel cover selection criterion for spatial steganography using linear pixel prediction error / Wei Huang, Xianfeng Zhao // Science China. Information Sciences. – 2016. – Vol. 59. – Pp. 059103:1–059103:3. DOI: 10.1007/s11432-016-5530-z
Tomáš Denemark. Improving Selection-Channel-Aware Steganalysis Features / Tomáš Denemark, Jessica Fridrich, Pedro Comesaña-Alfaro // IS&T International Symposium on Electronic Imaging 2016. – Pp. MWSF-080.1-MWSF-080.8.
NRCS Photo Gallery: [Электронный ресурс] // United States Department of Agriculture. Washington, USA. Режим доступа: http://photogallery.nrcs.usda.gov
Uncompressed Color Image Database (UCID) [Электронный ресурс]: Multimedia Phylogeny Datasets. Режим доступа: http://www.recod.ic.unicamp.br/~oikawa/datasets.html
McGill Calibrated Colour Image Database [Электронный ресурс]: Fred Kingdom's Laboratory at McGill Vision Research. Режим доступа: http://tabby.vision.mcgill.ca/html/welcome.html
Never-compressed image database [Электронный ресурс]: Sam Houston State University. Режим доступа: http://www.shsu.edu/qxl005/New/Downloads/
Ахмаметьева А.В. Стеганоанализ цифровых изображений, хранящихся в формате с потерями // Захист інформації. – 2016. – Вип. 23. – С.135-145.
Akhmametieva A. Steganalysis of digital contents, based on the analysis of unique color triplets // Annales Mathematicae et Informaticae. – 2017. – No.47. – Pp. 3-18.
Akhmametieva A. Method of detection the fact of compression in digital images as an integral part of steganalysis // Інформатика та математичні методи в моделюванні. – 2016. – Т.6. – №4. – С. 357-364.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).