21 March 2005 Unitary embedding for data hiding with the SVD
Author Affiliations +
Steganography is the study of data hiding for the purpose of covert communication. A secret message is inserted into a cover file so that the very existence of the message is not apparent. Most current steganography algorithms insert data in the spatial or transform domains; common transforms include the discrete cosine transform, the discrete Fourier transform, and discrete wavelet transform. In this paper, we present a data-hiding algorithm that exploits a decomposition representation of the data instead of a frequency-based transformation of the data. The decomposition transform used is the singular value decomposition (SVD). The SVD of a matrix A is a decomposition A= USV' in which S is a nonnegative diagonal matrix and U and V are orthogonal matrices. We show how to use the orthogonal matrices in the SVD as a vessel in which to embed information. Several challenges were presented in order to accomplish this, and we give effective information-hiding using the SVD can be just as effective as using transform-based techniques. Furthermore, different problems arise when using the SVD than using a transform-based technique. We have applied the SVD to image data, but the technique can be formulated for other data types such as audio and video.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Clifford Bergman, Clifford Bergman, Jennifer Davidson, Jennifer Davidson, } "Unitary embedding for data hiding with the SVD", Proc. SPIE 5681, Security, Steganography, and Watermarking of Multimedia Contents VII, (21 March 2005); doi: 10.1117/12.587796; https://doi.org/10.1117/12.587796


Data hiding in binary text documents
Proceedings of SPIE (July 31 2001)
Minimax eigenvector decomposition for data hiding
Proceedings of SPIE (September 16 2005)
Steganalysis with JPEG and GIF images
Proceedings of SPIE (June 21 2004)

Back to Top