Reversed-Mel cepstrum based audio steganalysis

Some of the previous audio steganalysis systems have suggested features based on human auditory system models. In contrast, this paper exploits the idea of maximum deviation from human auditory system to suggest an efficient audio steganalysis scheme. Based on this idea, an artificial ear is considered that has high resolution in high frequency region and low resolution where the frequency is low. Simulation results show that this artificial ear can virtually hear effect of steganography and distinguish between stego and clean audio signals. Proposed method achieves accuracy of 93% (StegHide@1.563% BPB) and 97% (Hide4Pgp@6.25% BPB) which are 16% and 12% higher than previous MFCC based methods.

[1]  H. Olson The Measurement of Loudness , 1972 .

[2]  Jana Dittmann,et al.  Mel-cepstrum-based steganalysis for VoIP steganography , 2007, Electronic Imaging.

[3]  Qingzhong Liu,et al.  Temporal Derivative-Based Spectrum and Mel-Cepstrum Audio Steganalysis , 2009, IEEE Transactions on Information Forensics and Security.

[4]  Tony R. Martinez,et al.  Improving classification accuracy by identifying and removing instances that should be misclassified , 2011, The 2011 International Joint Conference on Neural Networks.

[5]  Biswanath Mukherjee,et al.  A Novel Audio Steganalysis Based on High-Order Statistics of a Distortion Measure with Hausdorff Distance , 2008, ISC.

[6]  Siwei Lyu,et al.  Steganalysis of recorded speech , 2005, IS&T/SPIE Electronic Imaging.

[7]  Sergios Theodoridis,et al.  Pattern Recognition, Fourth Edition , 2008 .

[8]  Darko Kirovski,et al.  Spread-spectrum watermarking of audio signals , 2003, IEEE Trans. Signal Process..

[9]  Hugo Fastl,et al.  Psychoacoustics: Facts and Models , 1990 .

[10]  Mazdak Zamani,et al.  Correlation between PSNR and bit per sample rate in audio steganography , 2012 .

[11]  Emrah Yürüklü,et al.  Chaotic-Type Features for Speech Steganalysis , 2008, IEEE Transactions on Information Forensics and Security.

[12]  N. Kamaraj,et al.  Audio steganalysis with Hausdorff distance higher order statistics using a rule based decision tree paradigm , 2010, Expert Syst. Appl..

[13]  Yin-Cheng Qi,et al.  Wavelet domain audio steganalysis based on statistical moments and PCA , 2007, 2007 International Conference on Wavelet Analysis and Pattern Recognition.

[14]  Robert P. W. Duin,et al.  A Matlab Toolbox for Pattern Recognition , 2004 .

[15]  Douglas A. Reynolds,et al.  Robust text-independent speaker identification using Gaussian mixture speaker models , 1995, IEEE Trans. Speech Audio Process..

[16]  Ismail Avcibas Audio steganalysis with content-independent distortion measures , 2006, IEEE Signal Processing Letters.

[17]  Adam M. Croom Auditory Neuroscience: Making Sense of Sound , 2014 .

[18]  Nasir D. Memon,et al.  Detection of audio covert channels using statistical footprints of hidden messages , 2006, Digit. Signal Process..

[19]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[20]  Ingemar J. Cox,et al.  Secure spread spectrum watermarking for multimedia , 1997, IEEE Trans. Image Process..