<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The new common approach for integrity checking of digital images is developed. The new features of formal parameters defining image are revealed, theoretically grounded and practically tested. The characteristics of the mutual arrangement of left and right singular vectors corresponding to the largest singular value of the image’s matrix (block of matrix) and the vector composed of singular numbers is obtained. Formal parameters are obtained using normal singular decomposition of matrix (block of matrix) which is uniquely determined. It is shown that for most blocks of original image (no matter lossy or lossless) the angle between the left (right) mentioned singular vector and vector composed of singular numbers is defined by the angle between the n-optimal vector and the vector of standard basis of the range corresponding dimension. It is shown that the determined feature brakes for the mentioned formal parameters in a non-original image. This shows the integrity violation of the image, i.e. the existence of the additional information embedded using steganography algorithms. So this can be used as a basis for development of new universal steganography methods and algorithms, and one example of the realization is proposed. The efficiency of the proposed algorithm won’t depend on the details of steganography method used for embedding. All the obtained results can be easily adapted for the digital video and audio analysis.</p></abstract>

The new common approach for integrity checking of digital images is developed. The new features of formal parameters defining image are revealed, theoretically grounded and practically tested. The characteristics of the mutual arrangement of left and right singular vectors corresponding to the largest singular value of the image’s matrix (block of matrix) and the vector composed of singular numbers is obtained. Formal parameters are obtained using normal singular decomposition of matrix (block of matrix) which is uniquely determined. It is shown that for most blocks of original image (no matter lossy or lossless) the angle between the left (right) mentioned singular vector and vector composed of singular numbers is defined by the angle between the n-optimal vector and the vector of standard basis of the range corresponding dimension. It is shown that the determined feature brakes for the mentioned formal parameters in a non-original image. This shows the integrity violation of the image, i.e. the existence of the additional information embedded using steganography algorithms. So this can be used as a basis for development of new universal steganography methods and algorithms, and one example of the realization is proposed. The efficiency of the proposed algorithm won’t depend on the details of steganography method used for embedding. All the obtained results can be easily adapted for the digital video and audio analysis.

General Principles of Integrity Checking of Digital Images and Application for Steganalysis

Odessa National Polytechnic University Odessa, Ukraine, 1 Shevchenko Avenue

Transport and Telecommunication Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The new common approach for integrity checking of digital images is developed. The new features of formal parameters defining image are revealed, theoretically...

General Principles of Integrity Checking of Digital Images and Application for Steganalysis

Published Online: May 06, 2016

Page range: 128 - 137

DOI: https://doi.org/10.1515/ttj-2016-0012

Keywords
singular number, singular vector, n-optimal vector, normal singular decomposition, steganography analysis, steganalytical method

© Transport and Telecommunication Institute

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

General Principles of Integrity Checking of Digital Images and Application for Steganalysis

Published Online: May 06, 2016

Page range: 128 - 137

DOI: https://doi.org/10.1515/ttj-2016-0012

Keywordssingular number, singular vector, n-optimal vector, normal singular decomposition, steganography analysis, steganalytical method

© Transport and Telecommunication Institute

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
singular number, singular vector, n-optimal vector, normal singular decomposition, steganography analysis, steganalytical method