Abstract

In this study, a novel and high embedding capacity audio steganography scheme based on Lifting Wavelet Transform (LWT) and adaptive embedding positions is proposed. Specifically, the message data is inserted in the imperceptible positions that chosen from the coefficients of detail sub-bands taking advantage of our proposed Weighted Block Matching (WBM). The WBM is preceded by preparing the cover audio in order to select the bits-positions that can possibly be used for embedding from each detail coefficient based on coefficient amplitude then copy the contents of the selected bits-positions and arrange them in blocks of bits. Also, the message data is arranged in blocks of bits after preprocessed and encrypted. The WBM computes the matching between each message block and whole extracted cover blocks to find the similarity between them. This process help to provide optimal locations to hide the message blocks. These locations are considered as a stego-key that is ciphered and hided within the final detail sub-band which is specified for this purpose. The proposed approach attains higher security than other fixed embedding positions approaches because the random positions for the embedded message blocks based on adaptive selection for embedding positions. Experimental results show that the proposed technique is not only has very high embedding capacity (exceed 300 kbps) with excellent transparency (above 35 dB for the cover to noise ratio), but also achieve lossless massage retrieved. Comparisons with the related audio steganography algorithms also show that our proposed scheme outperforms all the selected algorithms.

Keywords:

Adaptive embedding positions, audio steganography, high embedding capacity, Lifting Wavelet Transform (LWT), Weighted Blocks Matching (WBM),

References

1. Bender, W., D. Gruhl, N. Morimoto and A. Lu, 1996. Techniques for data hiding. IBM Syst. J., 35(3-4): 313-336.
   CrossRef    
2. Cheddad, A., J. Condell, K. Curran and M.C. Kevitt, 2010. Digital image steganography: Survey and analysis of current methods. Signal Process., 90(3): 727-752.
   CrossRef    
3. Cvejic, N., 2004. Algorithms for audio watermarking and steganography. Ph.D. Thesis, Department of Electrical and Information Engineering, Information Processing Laboratory, University of Oulu, Oulu, Finland.
   
4. Cvejic, N. and T. Seppanen, 2002. A wavelet domain LSB insertion algorithm for high capacity audio steganography. Proceeding of 10th IEEE Digital Signal Processing Workshop and 2nd Signal Processing Education Workshop, pp: 53-55.
   CrossRef    
5. Cvejic, N. and T. Seppnen, 2004a. Reduced distortion bit-modification for LSB audio steganography. Proceeding of 7th International Conference on Signal Processing Proceedings (ICSP), Beijing, China, pp: 2320-2323.
   CrossRef    
6. Cvejic, N. and T. Seppanen, 2004b. Channel capacity of high bit rate audio data hiding algorithms in diverse transform domains. Proceeding of International Symposium on Communications and Information Technology (ISCIT), pp: 84- 88.
   CrossRef    
7. Delforouzi, A. and M. Pooyan, 2006. Adaptive digital audio steganography based on integer wavelet transform. Circ. Syst. Signal Pr. J., 27(2): 247-259.
   CrossRef    
8. Dewine, S. and J. Comelis, 1997. Lossless integer wavelet transform.IEEE Signal Proc. Let., 4(6): 158-160.
   CrossRef    
9. Djebbar, F., B. Ayad, H. Hamam and K. Abed-Meraim, 2011. A view on latest audio steganography techniques. Proceeding of IEEE International Conference of Innovations in Information Technology (IIT), pp: 409-414.
   CrossRef    
10. Ercelebi, E. and L. Batakc, 2009. Audio watermarking scheme based on embedding strategy in low frequency components with a binary image. Dig. Signal Process., 19(2): 265-277.
    CrossRef    
11. Geiger, R., Y. Yokotani and G. Schuller, 2006. Audio data hiding with high data rates based on intMDCT. Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing. Toulouse, pp: 205-208.
    CrossRef    
12. Huang, X., Y. Abe and I. Echizen, 2010. Capacity adaptive synchronized acoustic steganography scheme. J. Inform. Hiding Multimedia Signal Process., 1(2):72-90.
    
13. Lee, C. and C. Ko, 2011. Short-term load forecasting using lifting scheme and ARIMA models. Expert Syst. Appl., 38(5): 5902-5911.
    CrossRef    
14. Lei, B., I. Soon, F. Zhou, Z. Li and H. Lei, 2012. A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition. Signal Process., 92(9): 1985-2001.
    CrossRef    
15. Nissar, A. and A. Mir, 2010. Classification of steganalysis techniques: A study. Digit. Signal Process., 20(6): 1758-1770.
    CrossRef    
16. Pooyan, M. and A. Delforouzi, 2007. LSB-based audio steganography method based on lifting wavelet transform. Proceeding of 7th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT'07), pp: 600-603.
    CrossRef    
17. Shahadi, H.I. and R. Jidin, 2011. High capacity and in audibility Audio steganography scheme. Proceeding of 7th International Conference on Information Assurance and Security (IAS), pp: 104-109.
    
18. Shahreza, S. and M. Shalmani, 2007. Adaptive wavelet domain audio steganography with high capacity and low error rate. Proceeding of IEEE International Conference on Information and Emerging Technologies (ICIET), pp: 25-29.
    CrossRef    
19. Shahreza, S. and M. Shalmani, 2008. High capacity error free wavelet domain speech steganography. Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp: 1729-1732.
    CrossRef    
20. Wang, H. and S. Wang, 2004. Cyber warfare: Steganography vs. steganalysis. Commun. ACM, 47(10): 76-82.
    CrossRef    
21. Wang, J., R. Healy and J. Timoney, 2011. A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal. Signal Process., 91(1): 1693-1708.
    CrossRef    

Competing interests

The authors have no competing interests.

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