Title
An Svd-Based Adaptive Robust Speech Steganography Using Mdct Coefficient
Abstract
Speech is one of the essential ways of communication. The study of speech steganography provides great value in information security. To improve imperceptibility and robustness of speech steganography, the characteristics of speech signals should be fully taken into account. In this paper, a robust speech steganographic scheme based on Singular Value Decomposition (SVD) and Modified Discrete Cosine Transform (MDCT) is proposed. Firstly, Voice Activity Detector (VAD) is used to detect voiced frames from speech signals, along with MDCT with Kaiser Bessel Derived (KBD) window being performed on each frame. Then the MDCT coefficients are selected from a certain frequency range and divided into a pair of segments. The two largest singular values of the paired segments are modified respectively according to their value difference to embed secret message. The thresholds are adaptively adjusted according to the largest singular values. Extensive experiments are carried out to compare the proposed method with three other methods from imperceptibility, robustness, capacity, and security. The experimental results show that under the simulation parameters beta = 320,N-k= 58,f(l)= 100 Hz,f(h)= 3 kHz, and alpha= 0.61, the proposed method has striking advantages to resist common robust attacks and the state-of-the-art steganalysis attacks while maintaining good imperceptibility.
Year
DOI
Venue
2021
10.1007/s11042-020-09725-5
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Speech steganography, Voice activity detector, Modified discrete cosine transform, Singular value decomposition, Robustness
Journal
80
Issue
ISSN
Citations 
2
1380-7501
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Juan Wen1113.17
Hao Zeng284.60
yuzhu wang3146.71
Shurong Liu400.34
Yiming Xue5176.28