Steganalysis of content-adaptive JPEG steganography based on scale co-occurrence matrix with diverse quantization

Xiaoyan Xu; Xiaofeng Song; Chunfang Yang; Weiwei Zhao; Rongcai Zhao

doi:10.1117/1.JEI.27.6.063004

15 November 2018 Steganalysis of content-adaptive JPEG steganography based on scale co-occurrence matrix with diverse quantization

Xiaoyan Xu, Xiaofeng Song, Chunfang Yang, Weiwei Zhao, Rongcai Zhao

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 6, 063004 (November 2018). https://doi.org/10.1117/1.JEI.27.6.063004

Abstract

Feature extraction is very important for steganalysis of content-adaptive JPEG steganography. The scale co-occurrence matrix feature based on a two-dimensional (2-D) Gabor filter is proposed, and diverse quantization for filter residuals is utilized to improve the detection performance. First, the definition of scale co-occurrence matrix based on a 2-D Gabor filter is given and the rules for feature merge are analyzed. Then, the influence of the scale parameter and quantization step on the detection performance of the scale co-occurrence matrix feature is discussed and verified. Next, the effect of diverse quantization strategy is presented. Last, the detailed extraction process of the proposed steganalysis feature is described. The experimental results show that the proposed steganalysis feature can achieve a performance that is competitive with the state-of-the-art steganalysis features when used for the detection of the latest content-adaptive JPEG steganography algorithms.

Citation Download Citation

Xiaoyan Xu, Xiaofeng Song, Chunfang Yang, Weiwei Zhao, and Rongcai Zhao "Steganalysis of content-adaptive JPEG steganography based on scale co-occurrence matrix with diverse quantization," Journal of Electronic Imaging 27(6), 063004 (15 November 2018). https://doi.org/10.1117/1.JEI.27.6.063004

Received: 28 June 2018; Accepted: 24 October 2018; Published: 15 November 2018

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available