The Embedding Performance of StegSVM Model in Image Steganography

This paper focuses on one of the areas of information hiding which is image steganography. It proposes the StegSVM model as an embedding technique in steganography that has exploited human visual system through Shifted LSB that shows an expected performance. The performance of this technique evaluation is based on imperceptibility and robustness of the technique compared to the other previous models in image steganography doamin. Thus, the result shows that the proposed StegSVM model is promising. For further work, it is suggested that the other image domain through other intelligent methods should be investigated.

[1]  Nan Jiang A Novel Analysis Method of Information Hiding , 2008, 2008 Congress on Image and Signal Processing.

[2]  Eric Cole,et al.  Hiding in Plain Sight: Steganography and the Art of Covert Communication , 2003 .

[3]  Xuezeng Pan,et al.  A Blind Steganalytic Scheme Based on DCT and Spatial Domain for JPEG Images , 2010, J. Multim..

[4]  Zhenfu Cao,et al.  Survey of information security , 2007, Science in China Series F: Information Sciences.

[5]  Zheng Pei,et al.  A Novel Blind Image Watermarking Scheme Based on Support Vector Machine in DCT Domain , 2008, 2008 International Conference on Computational Intelligence and Security.

[6]  Huaiqing Wang,et al.  Cyber warfare: steganography vs. steganalysis , 2004, CACM.

[7]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[8]  Y.-S. Lai,et al.  Robust lossless image watermarking based on alpha-trimmed mean algorithm and support vector machine , 2010, J. Syst. Softw..

[9]  Min-Shiang Hwang,et al.  Data Hiding: Current Status and Key Issues , 2007, Int. J. Netw. Secur..

[10]  Adnan Abdul-Aziz Gutub,et al.  Pixel Indicator Technique for RGB Image Steganography , 2010 .

[12]  Jessica J. Fridrich,et al.  Feature-Based Steganalysis for JPEG Images and Its Implications for Future Design of Steganographic Schemes , 2004, Information Hiding.

[13]  Stefan A. Robila,et al.  Statistical steganalyis of images using open source software , 2010, 2010 IEEE Long Island Systems, Applications and Technology Conference.

[14]  Chih-Jen Lin,et al.  A Practical Guide to Support Vector Classication , 2008 .

[15]  Aman Jantan,et al.  A new steganography approach for image encryption exchange by using the least significant bit insertion , 2010, ICWET.

[16]  Lalit M. Patnaik,et al.  EMBEDDING INFORMATION IN DCT COEFFICIENTS BASED ON AVERAGE COVARIANCE , 2011 .

[17]  Azman Samsudin,et al.  A formulation of conditional states on steganalysis approach , 2012 .

[18]  Ruimin Shen,et al.  Reliable Information Hiding Based on Support Vector Machine , 2005, Informatica.

[19]  Chin-Chen Chang,et al.  A steganographic method based upon JPEG and quantization table modification , 2002, Inf. Sci..

[20]  E. Delp,et al.  Security, steganography, and watermarking of multimedia contents , 2004 .

[21]  Kevin Curran,et al.  Digital image steganography: Survey and analysis of current methods , 2010, Signal Process..

[22]  Bin Li,et al.  A Survey on Image Steganography and Steganalysis , 2011, J. Inf. Hiding Multim. Signal Process..

[23]  Roshidi Din,et al.  Preserve Imperceptibility and Robustness Performance on Steganography Technique based on StegaSVM-Shifted LBS Model , 2018 .