AN EXTENDED FEATURE SET FOR BLIND IMAGE STEGANALYSIS IN CONTOURLET DOMAIN

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SHAKERI EHSAN; GHAEMMAGHAMI SHAHROKH

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY Year:2014 | Volume:6 | Issue:2 Page(s): 169-181

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

464

Download:

160

Cites:

Information Journal Paper

Title

AN EXTENDED FEATURE SET FOR BLIND IMAGE STEGANALYSIS IN CONTOURLET DOMAIN

Author(s)

SHAKERI EHSAN | GHAEMMAGHAMI SHAHROKH | Issue Writer Certificate

Keywords

BLIND STEGANALYSISQ2

CONTOURLET TRANSFORMQ2

ZERNIKE MOMENTSQ2

CHARACTERISTIC FUNCTION MOMENTSQ2

STATISTICAL ANALYSISQ2

Abstract

The aim of image steganalysis is to detect the presence of hidden messages in stego images. We propose a blind image steganalysis method in Contourlet domain and then show that the embedding process changes statistics of Contourlet coefficients. The suspicious image is transformed into Contourlet space, and then the statistics of Contourlet subbands coefficients are extracted as features. We use absolute ZERNIKE MOMENTS and CHARACTERISTIC FUNCTION MOMENTS of Contourlet subbands coefficients of the image to distinguish between the stego and non-stego images. Absolute ZERNIKE MOMENTS are used to examine the randomness in the test image and CHARACTERISTIC FUNCTION MOMENTS of Contourlet coefficients is used to form our feature set that can catch the changes made to the histogram of Contourlet coefficients. These features are fed to a nonlinear SVM classifier with an RBF kernel to distinguish between cover and stego images. We show that the embedding process distorts statistics of Contourlet coefficients, leading to detection of stego images. Experimental results confirm that the proposed features are highly sensitive to the change made by the embedding process. These results also reveal advantage of the proposed method over its counterpart steganalyzers, in cases of five popular JPEG steganography techniques.

Cites

No record.

References

No record.

Cite

APA: Copy

SHAKERI, EHSAN, & GHAEMMAGHAMI, SHAHROKH. (2014). AN EXTENDED FEATURE SET FOR BLIND IMAGE STEGANALYSIS IN CONTOURLET DOMAIN. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, 6(2 ), 169-181. SID. https://sid.ir/paper/241793/en

Vancouver: Copy

SHAKERI EHSAN, GHAEMMAGHAMI SHAHROKH. AN EXTENDED FEATURE SET FOR BLIND IMAGE STEGANALYSIS IN CONTOURLET DOMAIN. THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY[Internet]. 2014;6(2 ):169-181. Available from: https://sid.ir/paper/241793/en

IEEE: Copy

EHSAN SHAKERI, and SHAHROKH GHAEMMAGHAMI, “AN EXTENDED FEATURE SET FOR BLIND IMAGE STEGANALYSIS IN CONTOURLET DOMAIN,” THE ISC INTERNATIONAL JOURNAL OF INFORMATION SECURITY, vol. 6, no. 2 , pp. 169–181, 2014, [Online]. Available: https://sid.ir/paper/241793/en

Related Journal Papers