Feature Based Steganalysis Using Wavelet Decomposition and Magnitude Statistics

Steganography is broadly used to embed information in high resolution images, since it can contain adequate information within the small portion of cover image. Steganalysis is the procedure of finding the occurrence of hidden message in an image. This paper compares the efficiency of two embedding algorithms using the image features that are consistent over a wide range of cover images, but are distributed by the presence of embedded data. Image features were extracted after wavelet decomposition of the given image. These features were then given to a SVM classifier to identify the stego content.

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

[2]  Rajarathnam Chandramouli,et al.  A mathematical framework for active steganalysis , 2003, Multimedia Systems.

[3]  Nasir D. Memon,et al.  Steganalysis using image quality metrics , 2003, IEEE Trans. Image Process..

[4]  Siwei Lyu,et al.  Steganalysis using higher-order image statistics , 2006, IEEE Transactions on Information Forensics and Security.

[5]  Jessica J. Fridrich,et al.  Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics , 2005, Communications and Multimedia Security.

[6]  Rajarathnam Chandramouli,et al.  Current trends in steganalysis: a critical survey , 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..

[7]  Min Wu,et al.  Noise Features for Image Tampering Detection and Steganalysis , 2007, 2007 IEEE International Conference on Image Processing.