NDLI: Time domain speech steganalysis method based on multiplicative embedding model

Content Provider	IEEE Xplore Digital Library
Author	Liang Ye Xiu-Juan Qi Lin-Jie Lv Yi Zuo
Copyright Year	2012
Description	Author affiliation: Department of Information Engineering and Management, North China Baoding Electric Power Vocational and Technical, College, Baoding 071051, China (Liang Ye; Xiu-Juan Qi; Lin-Jie Lv; Yi Zuo)
Abstract	Steganalysis is detecting and decoding hidden data within a given media and is taken as a countermeasure to steganography. There has been quite some effort in audio steganalysis for additive embedding model. But, results are disappointing when they distinguish the cover-audio signal with multiplicative noise and the stego-audio signal. In this paper, multiplicative noise is changed to additive noise. A time domain audio steganalysis method for multiplicative embedding model is proposed. The test audio signal is calculated its absolute value and logarithm at first. Then features are extracted. Then, 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 89%. The method is effective.
Starting Page	148
Ending Page	151
File Size	862454
Page Count	4
File Format	PDF
ISBN	9781467315340
ISSN	21585695
e-ISBN	9781467315357
DOI	10.1109/ICWAPR.2012.6294769
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Additive noise Training Steganalysis Support vector machine classification Time domain analysis Time domain Feature extraction SVM Multiplicative model Audio
Content Type	Text
Resource Type	Article

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