DocumentCode :
1896393
Title :
Effective Steganalysis of YASS Based on Statistical Moments of Wavelet Characteristic Function and Markov Process
Author :
Xiang Yang ; Zhang Wen-hua
Author_Institution :
First Dept., Xi´an Commun. Inst., Xi´an, China
Volume :
1
fYear :
2012
fDate :
23-25 March 2012
Firstpage :
606
Lastpage :
610
Abstract :
A promising steganograhic method-Yet Another Steganographic Scheme(YASS) was designed to resist calibration based blind steganalysis via embedding data in randomized locations. The existing steganalysis methods analyze it ineffectively or use high-dimensional feature set or are targeted steganalysis methods. In this paper, we present a steganalysis method of lower-dimensional feature sets, and it can effectively detect YASS. The 198-dimensional feature vector is calculated in the wavelet domain as statistical moments of wavelet characteristic function and Markov process features of low frequency coefficients. A SVM based classifier is trained on the extracted features for the detection of the presence of steganography. Experimental results show that the new feature set provides significantly better results for detecting YASS than previous art.
Keywords :
Markov processes; calibration; feature extraction; image classification; image coding; steganography; support vector machines; vectors; wavelet transforms; Markov process; SVM based classifier; calibration based blind steganalysis; feature extraction; feature vector; randomized location; statistical moment; steganograhic method; wavelet characteristic function; wavelet domain; yet another steganographic scheme; Arrays; Discrete cosine transforms; Feature extraction; Histograms; Markov processes; Transform coding; Wavelet domain; Markov process; Wavelet transform; YASS;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-0689-8
Type :
conf
DOI :
10.1109/ICCSEE.2012.218
Filename :
6187919
Link To Document :
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