High Capacity Audio Steganography Based on Contourlet Transform
Article Sidebar
Main Article Content
Abstract
The science of hiding information behind other cover media file is known
steganography. Audio steganography means that a secret message is hidden by
embedding it in an audio file. This paper presents a new audio steganography
approach that is used the contourlet transform to hide a speech and image in an
audio signal. The cover audio signal is modified to be suitable as input to contourlet
transform and then secret data embed to the subbands of contourlet transform. The
results showed high hiding capacity of data up to 90% of cover audio file size. In
addition, performance analysis by measures factors: Normalized Correlation (NC),
Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR) appears good
quality results for both stego and secret data.
Metrics
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY LICENSE http://creativecommons.org/licenses/by/4.0/
Plaudit
References
Tayel M, Gamal A, Shawky A. A proposed
implementation method of an audio steganography
technique. The 18th International Conference on
Advanced Communication Technology (ICACT2016),
IEEE 2016, 31 January-3 February; Pyeong Chang,
South Korea; pp. 180 –184.
Jisna VA, Sobin CC. A new proposal for audio
steganography in wavelet domain. The IEEE Fourth
International Conference on Advances in Recent
Technologies Communication and Computing
(ARTCom2012) 2012 October 19-20; Bangalore,
India; pp. 310–312.
Parab N, Nathan M, Talele KT. Audio steganography
using differential phase encoding. Heidelberg,
Germany: Technology Systems and Management;
Djebbar F, Ayad B, AbedMeraim K, Hamam H.
Comparative study of digital audio steganography
techniques. EURASIP Journal on Audio, Speech, and
Music Processing 2012; 25: 1-16.
Mohan M, Anurenjan PR. A new algorithm for data
hiding in images using contourlet transform. The
Recent Advances in Intelligent Computational
Systems (RAICS) 2011 September 22-24;
Trivandrum, India; pp. 411–415.
Gopalan K, Shi Q. Audio steganography using bit
modification-a tradeoff on perceptibility and data
robustness for large payload audio embedding.
The19th International Conference on Computer
Communications and Networks (ICCCN2010), 2010
August 2-5; Zurich, Switzerland: pp. 1–6.
Gopalan K, Wenndt S, Noga A, Haddad D, Adams S.
Covert speech communication via cover speech by
tone insertion. IEEE Aerospace Conference
Proceedings 2003 March 8-15; Montana, USA: pp.
-1653.
Nugraha RM. Implementation of direct sequence
spread spectrum steganography on audio data. The
International Conference on Electrical Engineering
and Informatics (ICEEI) 2011 July 17-19; Bandung,
Indonesia, IEEE: pp. 1-6.
Shahreza SS, Manzuri-Shalmani MT. High capacity
error free wavelet domain speech steganography.
IEEE 2008 International Conference on Acoustics,
Speech and Signal Processing 2008 March 31- April
; Las Vegas, NV, USA, IEEE: pp. 1729 -1732.
Prasad GS, Varadarajan S. A novel hybrid audio
steganography for imperceptible data hiding. The
International Conference on Communications and
Signal Processing (ICCSP) 2015 April 2-4;
Melmaruvathur, India, IEEE: pp. 0634 – 0638.
Do MN, Vetterli M. The contourlet transform: an
efficient directional multiresolution image
representation. IEEE Transactions on Image
Processing 2005; 14: 2091-2106. DOI: https://doi.org/10.1109/TIP.2005.859376
Shahadi HI, Jidin R. High capacity and inaudibility
audio steganography scheme. 7th International
Conference on Information Assurance and Security
(IAS) 2011 December 5-8; Melaka, Malaysia, IEEE:
pp. 104-109.
Verma SS, Gupta R, Shrivastava G. A novel
technique for data hiding in audio carrier by using
sample comparison in dwt domain. Fourth
International Conference on Communication Systems Abbas Salman Hameed / Tikrit Journal of Engineering Sciences 25 (1) 2018 (1-7) 7
and Network Technologies 2014 April 7-9; Bhopal,
India, IEEE: pp. 639-643.
Do M, Vetterli M. Framing pyramids. IEEE
Transactions on Signal Processing 2003; 51: 2329- DOI: https://doi.org/10.1109/TSP.2003.815389
Rabizadeh M, Amirmazlaghani M, Attari MA. A new
detector for contourlet domain multiplicative image
watermarking using Bessel K form distribution.
Journal of Visual Communication and Image
Representation 2016; 40:324–334. DOI: https://doi.org/10.1016/j.jvcir.2016.07.001
Guo D, Chen J. The application of contourlet
transform to image denoising. Advanced in Control
Engineering and Information Science 2011, 15, 2333- DOI: https://doi.org/10.1016/j.proeng.2011.08.437
Uma G, Selvi V, Nadarajan R. Coronary angiogram
video compression using wavelet-based contourlet
transform and region-of-interest technique. IET
Image Processing 2012; 6: 1049–1056. DOI: https://doi.org/10.1049/iet-ipr.2011.0284
Jin R, Yin J, Zhou W, Yang J. Improved multiscale
edge detection method for polarimetric SAR images.
IEEE Geoscience and Remote Sensing Letters 2016;
: 1104-1108.
Chen X, Liu L. Contourlet-2.3 retrieval algorithm
using absolute mean energy and kurtosis features.
Advanced Electrical and Electronics Engineering
, 87, 319-326.
Wei SD, Lai SH. Fast template matching algorithm
based on normalized cross correlation with adaptive
multilevel winner update. IEEE Transactions on
Image Processing 2008, 17, 2227-2235 DOI: https://doi.org/10.1109/TIP.2008.2004615