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Steganalysis for JPEG Images Based on Statistical Features of Stego and Cover Images.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
De-Shuang Huang
Heutte, Laurent
Loog, Marco
Xiaomei Quan
Hongbin Zhang
Source :
Advanced Intelligent Computing Theories & Applications. With Aspects of Theoretical & Methodological Issues; 2007, p970-977, 8p
Publication Year :
2007

Abstract

According to Cachin's steganography security criterion, if the statistical distributions of cover and stego images are identical, the hidden message is assumed undetectable. However, any steganographic method will surely cause some statistical distortions, which gives steganalyst a hint. This paper presents a steganalysis method for JPEG images based on Cachin criterion. It estimates the cover image from the stego one by using a small-scale geometrical transform, and then detects the statistical distortions between the cover and stego images based on some features, which are sensitive to the steganographic modifications. Then a classifier is trained on these features. Three different modern steganographic schemes are tested. Experimental results show that the proposed steganalysis scheme has better performance compared to the current steganalysis methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540741701
Database :
Complementary Index
Journal :
Advanced Intelligent Computing Theories & Applications. With Aspects of Theoretical & Methodological Issues
Publication Type :
Book
Accession number :
33100780
Full Text :
https://doi.org/10.1007/978-3-540-74171-8_98