Steganalysis of Adaptive Multi-Rate Speech Based on Extreme Gradient Boosting

Steganalysis of Adaptive Multi-Rate Speech Based on Extreme Gradient Boosting

Steganalysis of adaptive multi-rate (AMR) speech is a hot topic for controlling cybercrimes grounded in steganography in related speech streams. In this paper, we first present a novel AMR steganalysis model, which utilizes extreme gradient boosting (XGBoost) as the classifier, instead of support ve...

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Bibliographic Details
Main Authors: Congcong Sun, Hui Tian, Chin-Chen Chang, Yewang Chen, Yiqiao Cai, Yongqian Du, Yong-Hong Chen, Chih Cheng Chen
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Electronics
Subjects:
steganalysis
steganography
convergence feature
extreme gradient trees
adaptive multi-rate speech
Online Access:https://www.mdpi.com/2079-9292/9/3/522

Internet

https://www.mdpi.com/2079-9292/9/3/522

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