Perceptual threshold in DWT for optimum embedding rate in data hiding using HVS and GA

Steganography is the process of concealing data to protect the carrier file data from intruders. One of the main challenges of steganography is to maintain optimum visual quality while increasing hiding capacity. This can be resolved by incorporating the human visual systems weaknesses in steganography, which results in a good quality of the algorithm. Additionally, steganography is considered as an optimization problem to obtain optimum embedding rate. For this reason, this paper presents a novel method aimed towards a selection of perceptual embedding threshold in Discrete Wavelet Transform using human visual system characteristics and Genetic Algorithm. This method included an introduction of an optimization model by maintaining a correlation between neighboring areas of the image and the different parts of the object. The results of the experiment involving a variety of two thousand images show the differences between the various methods and the HVS in relation to accuracy. Furthermore, higher levels of detectability and comprehensiveness were seen. Lastly, the method has a high tendency to maintain image quality as well as the transparency when subjected to steganography.

[1]  D. Artz,et al.  Digital steganography: hiding data within data , 2001 .

[2]  Q. Gu,et al.  Reversible watermarking algorithm based on wavelet lifting scheme , 2007, 2007 International Conference on Wavelet Analysis and Pattern Recognition.

[3]  Kefa Rabah,et al.  Steganography-The Art of Hiding Data , 2004 .

[4]  Zenon Chaczko,et al.  Hyper Edge Detection with Clustering for Data Hiding , 2016, J. Inf. Hiding Multim. Signal Process..

[5]  Jamshid Shanbehzadeh,et al.  High Capacity Image Steganography Based on Genetic Algorithm and Wavelet Transform , 2012 .

[6]  Ajith Abraham,et al.  Significance of steganography on data security , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

[7]  Wen-Nung Lie,et al.  Data hiding in images with adaptive numbers of least significant bits based on the human visual system , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[8]  Shen Wang,et al.  A Secure Steganography Method based on Genetic Algorithm , 2010, J. Inf. Hiding Multim. Signal Process..

[9]  Ingemar J. Cox,et al.  Digital Watermarking and Steganography , 2014 .

[10]  Zengqiang Chen,et al.  A Novel Adaptive Reversible Watermarking Algorithm Based on Wavelet Lifting Scheme , 2009, 2009 International Conference on Information Engineering and Computer Science.

[11]  Kee-Young Yoo,et al.  A New Image Steganography Based on 2k Correction and Edge-Detection , 2008, Fifth International Conference on Information Technology: New Generations (itng 2008).

[12]  Ronak Karimi,et al.  Steganography in Image Segments Using Genetic Algorithm , 2015, 2015 Fifth International Conference on Advanced Computing & Communication Technologies.

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

[14]  Zenon Chaczko,et al.  Digital multimedia archiving based on optimization steganography system , 2014, 2014 Asia-Pacific Conference on Computer Aided System Engineering (APCASE).

[15]  Nikolay N. Ponomarenko,et al.  A NEW FULL-REFERENCE QUALITY METRICS BASED ON HVS , 2006 .

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

[17]  Jun Li,et al.  Steganography based on Minimizing Embedding Impact function and HVS , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).