Universal image steganalysis based on GARCH model

This paper introduces a new universal steganalysis framework. The required image features are extracted based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and higher-order statistics of the images. The GARCH features are extracted from non-approximate wavelet coeffi...

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Bibliographic Details
Main Authors: Akhavan, Saeed, Ali Akhaee, Mohammad, Sarreshtedari, Saeed
Format: Conference Proceeding
Language:English
Subjects:
Correlation
Discrete cosine transforms
Feature extraction
GARCH Model
Higher order statistics
Steganalysis
Training
Wavelet transforms
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Summary:This paper introduces a new universal steganalysis framework. The required image features are extracted based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and higher-order statistics of the images. The GARCH features are extracted from non-approximate wavelet coefficients. Besides, the second and third order statistics are exploited to develop features very sensitive to minor changes in natural images. The experimental results demonstrate that the proposed feature-based steganalysis framework outperforms state of the art methods while running on the same order of features.
ISSN:2219-5491
2219-5491