Audio Steganalysis Based on Co-occurrence Matrix and PCA

Author

Qi Yinchen ; Wang Yan ; Yuan Jinsha

Author_Institution

Dept. of Electron. & Commun. Eng., North China Electr. Power Univ., Baoding, China

Volume

1

fYear

2009

Firstpage

433

Lastpage

436

Abstract

A new steganalysis scheme based on co-occurrence matrix for audio signals is proposed. The statistics features are derived from the co-occurrence matrix firstly, which are calculated from amplitude of audio signals. Then the preprocessing of principal component analysis (PCA) is used on statistics features and the support vector machine (SVM) is used as a classifier. Experiment results for 450 audio signals of CASIA98-99 audio database show that the detection rates of three audio data hidden methods (wavelet domain least significant bit, quantization index method and addition method) are all greater than 92%.

Keywords

audio coding; audio signals; matrix algebra; principal component analysis; signal classification; steganography; support vector machines; CASIA98-99 audio database; PCA; SVM classifier; addition method; audio data hidden method; audio signal amplitude; audio steganalysis; co-occurrence matrix; principal component analysis; quantization index method; statistical feature; support vector machine; wavelet domain least significant bit method; Arithmetic; Distortion measurement; Feature extraction; Principal component analysis; Signal processing; Statistics; Steganography; Support vector machine classification; Support vector machines; Testing; PCA; SVM; co-occurrence matrix; steganalysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on

Print_ISBN

978-0-7695-3583-8

Type

conf

DOI

10.1109/ICMTMA.2009.342

Filename

5203005