Detecting Steganography of Adaptive Multirate Speech with Unknown Embedding Rate
Joint Authors
Huang, Y.
Wang, Tian
Tian, Hui
Sun, Jun
Chen, Yonghong
Cai, Yiqiao
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-18
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Telecommunications Engineering
Abstract EN
Steganalysis of adaptive multirate (AMR) speech is a significant research topic for preventing cybercrimes based on steganography in mobile speech services.
Differing from the state-of-the-art works, this paper focuses on steganalysis of AMR speech with unknown embedding rate, where we present three schemes based on support-vector-machine to address the concern.
The first two schemes evolve from the existing image steganalysis schemes, which adopt different global classifiers.
One is trained on a comprehensive speech sample set including original samples and steganographic samples with various embedding rates, while the other is trained on a particular speech sample set containing original samples and steganographic samples with uniform distributions of embedded information.
Further, we present a hybrid steganalysis scheme, which employs Dempster–Shafer theory (DST) to fuse all the evidence from multiple specific classifiers and provide a synthesized detection result.
All the steganalysis schemes are evaluated using the well-selected feature set based on statistical characteristics of pulse pairs and compared with the optimal steganalysis that adopts specialized classifiers for corresponding embedding rates.
The experimental results demonstrate that all the three steganalysis schemes are feasible and effective for detecting the existing steganographic methods with unknown embedding rates in AMR speech streams, while the DST-based scheme outperforms the others overall.
American Psychological Association (APA)
Tian, Hui& Sun, Jun& Huang, Y.& Wang, Tian& Chen, Yonghong& Cai, Yiqiao. 2017. Detecting Steganography of Adaptive Multirate Speech with Unknown Embedding Rate. Mobile Information Systems،Vol. 2017, no. 2017, pp.1-18.
https://search.emarefa.net/detail/BIM-1189102
Modern Language Association (MLA)
Tian, Hui…[et al.]. Detecting Steganography of Adaptive Multirate Speech with Unknown Embedding Rate. Mobile Information Systems No. 2017 (2017), pp.1-18.
https://search.emarefa.net/detail/BIM-1189102
American Medical Association (AMA)
Tian, Hui& Sun, Jun& Huang, Y.& Wang, Tian& Chen, Yonghong& Cai, Yiqiao. Detecting Steganography of Adaptive Multirate Speech with Unknown Embedding Rate. Mobile Information Systems. 2017. Vol. 2017, no. 2017, pp.1-18.
https://search.emarefa.net/detail/BIM-1189102
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189102