Steganalysis by subtractive pixel adjacency matrix

This paper presents a method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching. First, arguments are provided for modeling the differences between adjacent pixels using first-order and second-order Markov chains. Subsets of sample transition probability matrices are then used as features for a steganalyzer implemented by support vector machines. The major part of experiments, performed on four diverse image databases, focuses on evaluation of detection of LSB matching. The comparison to prior art reveals that the presented feature set offers superior accuracy in detecting LSB matching. Even though the feature set was developed specifically for spatial domain steganalysis, by constructing steganalyzers for ten algorithms for JPEG images, it is demonstrated that the features detect steganography in the transform domain as well.

[1]  Masoud Nikravesh,et al.  Feature Extraction - Foundations and Applications , 2006, Feature Extraction.

[2]  B. S. Manjunath,et al.  Steganalysis of spread spectrum data hiding exploiting cover memory , 2005, IS&T/SPIE Electronic Imaging.

[3]  Jessica J. Fridrich,et al.  Calibration revisited , 2009, MM&Sec '09.

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

[5]  Jessica J. Fridrich,et al.  Maximum likelihood estimation of length of secret message embedded using ±k steganography in spatial domain , 2005, IS&T/SPIE Electronic Imaging.

[6]  Tomás Pevný,et al.  Steganalysis by Subtractive Pixel Adjacency Matrix , 2009, IEEE Transactions on Information Forensics and Security.

[7]  Andrew D. Ker.  A General Framework for Structural Steganalysis of LSB Replacement , 2005, Information Hiding.

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

[9]  Tomás Pevný,et al.  Statistically undetectable jpeg steganography: dead ends challenges, and opportunities , 2007, MM&Sec.

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

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

[12]  Tieyong Zeng,et al.  Detecting LSB matching by applying calibration technique for difference image , 2008, MM&Sec '08.

[13]  Dana S. Richards,et al.  Modified Matrix Encoding Technique for Minimal Distortion Steganography , 2006, Information Hiding.

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

[15]  Rainer Böhme,et al.  Revisiting weighted stego-image steganalysis , 2008, Electronic Imaging.

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

[17]  Tomás Pevný,et al.  From Blind to Quantitative Steganalysis , 2012, IEEE Trans. Inf. Forensics Secur..

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

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

[20]  Andrew D. Ker,et al.  Feature reduction and payload location with WAM steganalysis , 2009, Electronic Imaging.

[21]  Tomás Pevný,et al.  Multiclass Detector of Current Steganographic Methods for JPEG Format , 2008, IEEE Transactions on Information Forensics and Security.

[22]  Kannan Ramchandran,et al.  Low-complexity image denoising based on statistical modeling of wavelet coefficients , 1999, IEEE Signal Processing Letters.

[23]  David Mumford,et al.  Statistics of natural images and models , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[24]  Andrew D. Ker.  A Fusion of Maximum Likelihood and Structural Steganalysis , 2007, Information Hiding.

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

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

[27]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[28]  Le Song,et al.  Supervised feature selection via dependence estimation , 2007, ICML '07.

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

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

[31]  Amaury Lendasse,et al.  Reliable Steganalysis Using a Minimum Set of Samples and Features , 2009, EURASIP J. Inf. Secur..

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

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

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

[35]  Andrew D. Ker.  Steganalysis of LSB matching in grayscale images , 2005, IEEE Signal Processing Letters.

[36]  Ingemar J. Cox,et al.  A comparative study of ± steganalyzers , 2008, 2008 IEEE 10th Workshop on Multimedia Signal Processing.

[37]  Ingemar J. Cox,et al.  Detection of ±1 LSB steganography based on the amplitude of histogram local extrema , 2008, 2008 15th IEEE International Conference on Image Processing.

[38]  Petra Mutzel,et al.  A Graph-Theoretic Approach to Steganography , 2005, Communications and Multimedia Security.

[39]  Jessica J. Fridrich,et al.  Digital image steganography using stochastic modulation , 2003, IS&T/SPIE Electronic Imaging.

[40]  Wei Su,et al.  Steganalysis based on Markov Model of Thresholded Prediction-Error Image , 2006, 2006 IEEE International Conference on Multimedia and Expo.

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

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