BSS: Boosted steganography scheme with cover image preprocessing

The existing powerful steganalyzers can find out the presence of secret information in images with high accuracy. Increasing the embedding capacity of cover images reduces the detection risk of stego images. In this respect, we introduce boosted steganography scheme (BSS) that has a preprocessing stage before applying steganography methods. The goal of BSS is increasing the undetectability of stego images. Due to the dependence of embedding capacity of images to their content, we proposed an ensemble steganalyzer to estimate the embedding capacity of each cover image. Since the content of cover images has less significance in steganography, therefore to have more security, the steganographer can select a cover image from a database to achieve higher security and satisfactory embedding capacity. We present several experiments that show the effectiveness of boosted steganography scheme in improving the security of stego images. The experimental results demonstrate that considering a preprocessing stage can significantly improve the steganography security.

[1]  Yan-Shi Dong,et al.  Boosting SVM classifiers by ensemble , 2005, WWW '05.

[2]  Tomás Pevný,et al.  Merging Markov and DCT features for multi-class JPEG steganalysis , 2007, Electronic Imaging.

[3]  Anindya Sarkar,et al.  YASS: Yet Another Steganographic Scheme That Resists Blind Steganalysis , 2007, Information Hiding.

[4]  Lisa M. Marvel,et al.  Spread spectrum image steganography , 1999, IEEE Trans. Image Process..

[5]  Kurt Hornik,et al.  The support vector machine under test , 2003, Neurocomputing.

[6]  Ingvar Claesson,et al.  Gray-scale image enhancement using the SMQT , 2005, IEEE International Conference on Image Processing 2005.

[7]  Tomás Pevný,et al.  Novelty detection in blind steganalysis , 2008, MM&Sec '08.

[8]  M. Jamzad,et al.  A robust steganography algorithm based on texture similarity using Gabor filter , 2005, Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005..

[9]  Thomas G. Dietterich Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[10]  Siwei Lyu,et al.  Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines , 2002, Information Hiding.

[11]  Guillermo Sapiro,et al.  Is image steganography natural? , 2005, IEEE Transactions on Image Processing.

[12]  Ralph Stephen Haller Complexity of real images evaluated by densitometric analysis and by psychophysical scaling , 1970 .

[13]  Andreas Westfeld,et al.  F5-A Steganographic Algorithm , 2001, Information Hiding.

[14]  Zhongmin Liu,et al.  The effect of image enhancement on biomedical pattern recognition , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[15]  M. Jamzad,et al.  Adaptive steganography method based on contourlet transform , 2008, 2008 9th International Conference on Signal Processing.

[16]  Wen-Rong Wu,et al.  Image Contrast Enhancement Based on a Histogram Transformation of Local Standard Deviation , 1998, IEEE Trans. Medical Imaging.

[17]  Jessica J. Fridrich,et al.  Perturbed quantization steganography with wet paper codes , 2004, MM&Sec '04.

[18]  Hedieh Sajedi,et al.  Cover Selection Steganography Method Based on Similarity of Image Blocks , 2008, 2008 IEEE 8th International Conference on Computer and Information Technology Workshops.

[19]  Phil Sallee,et al.  Model-Based Steganography , 2003, IWDW.

[20]  Yun Q. Shi,et al.  Statistical Moments Based Universal Steganalysis using JPEG 2-D Array and 2-D Characteristic Function , 2006, 2006 International Conference on Image Processing.

[21]  Zixiang Xiong,et al.  Image enhancement using multiscale differential operators , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[22]  Ingvar Claesson,et al.  The successive mean quantization transform , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..