Effective Steganalysis of YASS Based on Statistical Moments of Wavelet Characteristic Function and Markov Process

A promising steganograhic method-Yet Another Steganographic Scheme(YASS) was designed to resist calibration based blind steganalysis via embedding data in randomized locations. The existing steganalysis methods analyze it ineffectively or use high-dimensional feature set or are targeted steganalysis methods. In this paper, we present a steganalysis method of lower-dimensional feature sets, and it can effectively detect YASS. The 198-dimensional feature vector is calculated in the wavelet domain as statistical moments of wavelet characteristic function and Markov process features of low frequency coefficients. A SVM based classifier is trained on the extracted features for the detection of the presence of steganography. Experimental results show that the new feature set provides significantly better results for detecting YASS than previous art.

[1]  Bin Li,et al.  Steganalysis of YASS , 2009, IEEE Transactions on Information Forensics and Security.

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

[3]  William A. Pearlman,et al.  Steganalysis of additive-noise modelable information hiding , 2003, IS&T/SPIE Electronic Imaging.

[4]  Jessica J. Fridrich,et al.  New blind steganalysis and its implications , 2006, Electronic Imaging.

[5]  Tomás Pevný,et al.  Modern steganalysis can detect YASS , 2010, Electronic Imaging.

[6]  Noboru Babaguchi,et al.  Breaking the YASS algorithm via pixel and DCT coefficients analysis , 2008, 2008 19th International Conference on Pattern Recognition.

[7]  Tomás Pevný,et al.  Steganalysis by subtractive pixel adjacency matrix , 2010, IEEE Trans. Inf. Forensics Secur..

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

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

[10]  Chengyun Yang,et al.  Steganalysis Based on Multiple Features Formed by Statistical Moments of Wavelet Characteristic Functions , 2005, Information Hiding.

[11]  Jessica J. Fridrich,et al.  Writing on wet paper , 2005, IEEE Transactions on Signal Processing.

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

[13]  Yun Q. Shi,et al.  A Markov Process Based Approach to Effective Attacking JPEG Steganography , 2006, Information Hiding.

[14]  Anindya Sarkar,et al.  Further study on YASS: steganography based on randomized embedding to resist blind steganalysis , 2008, Electronic Imaging.

[15]  Mauro Barni,et al.  A Comparative Study of ±1 Steganalyzers , 2008 .

[16]  Jessica J. Fridrich,et al.  Influence of embedding strategies on security of steganographic methods in the JPEG domain , 2008, Electronic Imaging.

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