DocumentCode :
3019754
Title :
Wavelet domain audio steganalysis for multiplicative embedding model
Author :
Qi, Yin-cheng ; Ye, Liang ; Liu, Chong
Author_Institution :
Dept. of Electron. & Commun. Eng., North Electr. Power Univ., Baoding, China
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
429
Lastpage :
432
Abstract :
Steganalysis is taken as a countermeasure to steganography and is detecting and decoding hidden data within a given media. There has been quite some effort in audio steganalysis for additive embedding model. However, when they distinguish the cover-audio signal with multiplicative noise and the stego-audio signal, results are disappointing. In this paper, a wavelet domain audio steganalysis method for multiplicative embedding model is proposed. The test audio signal is firstly calculated its absolute value and logarithm. Multiplicative noise is changed to additive noise. Then features are extracted. At last, support vector machine (SVM) is utilized as a classifier to distinguish the cover-audio signal and the stego-audio signal. Simulation results show that the detection rates are greater than 94% and the method is effective.
Keywords :
audio signal processing; steganography; support vector machines; wavelet transforms; additive embedding model; hidden data decoding; hidden data detection; multiplicative embedding model; steganography; support vector machine; wavelet domain audio steganalysis; Additive noise; Feature extraction; Frequency domain analysis; Histograms; Pattern analysis; Steganography; Support vector machine classification; Support vector machines; Wavelet analysis; Wavelet domain; Audio; Multiplicative embedding model; SVM; Steganalysis; Wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3728-3
Electronic_ISBN :
978-1-4244-3729-0
Type :
conf
DOI :
10.1109/ICWAPR.2009.5207432
Filename :
5207432
Link To Document :
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