Blind Steganalysis using Wavelet Statistics and ANOVA

Author

Zhan, Shuang-Huan ; Zhang, Hong-bin

Author_Institution

Beijing Univ. of Technol., Beijing

Volume

5

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

2515

Lastpage

2519

Abstract

Blind steganalysis detects hidden message without any knowledge about steganographic method. To implement blind steganalysis, statistical model based on high-order wavelet decomposition is built to capture statistical difference between cover images and stego images. However, not all wavelet statistics are able to reflect well statistical changes due to hidden message embedded. Analysis of variance (ANOVA) is applied to test which wavelet statistics are more sensitive to hidden message. The statistics that are sensitive to hidden message are selected as image´s features. Using support vector machine (SVM) as classifier, our experiment results show that ANOVA is effective and our method effectively improves accuracy.

Keywords

cryptography; data encapsulation; image classification; support vector machines; ANOVA; SVM classifier; blind steganalysis; cover images; hidden blind message; high-order wavelet decomposition; steganography; stego images; support vector machine; variance analysis; wavelet statistics; Analysis of variance; Cybernetics; Machine learning; Statistical analysis; Statistical distributions; Statistics; Steganography; Support vector machine classification; Support vector machines; Testing; Analysis of variance; Blind steganalysis; Steganographic; Support vector machine; Wavelet statistic;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370570

Filename

4370570