NDLI: A wavelet-based blind JPEG image steganalysis using co-occurrence matrix

Content Provider	IEEE Xplore Digital Library
Author	Han Zong Fenlin Liu Xiangyang Luo
Copyright Year	2009
Description	Author affiliation: Information Science and Technology Institute, Zhengzhou, China, 450002 (Han Zong; Fenlin Liu; Xiangyang Luo)
Abstract	A new approach to blind detection of JPEG images having hiding information, which is based on the feature of wavelet domain is put forward. The specific way of detection is as follows: First, decompose an image by using wavelet, calculate the co-occurrence matrix of the adjacent wavelet coefficients, and apply Laplace transform to the co-occurrence matrix. Then take the Laplace-transformed variances and characteristic function (CF) moments of the co-occurrence matrix as the statistical feature, and choose BP neural network classifiers to classify and detect. Experiments of detecting the four typical steganographic algorithms of Jsteg, F5, Jphide and Outguess in such JPEG images have been carried out at different embedded ratios by using the method mentioned in this article, and the results show that the blind detecting method has the higher accuracy and it has higher calculating speed compared with the typical blind detecting methods.
Starting Page	1933
Ending Page	1936
File Size	2575936
Page Count	4
File Format	PDF
ISBN	9788955191387
ISSN	17389445
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-15
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Electronics and Telecommunications Research Institute
Subject Keyword	Wavelet domain Matrix decomposition Steganography Statistics Wavelet coefficients Laplace equations Change detection algorithms Probability Information science Neural networks Lalas transformation Blind steganalysis co-occurrence matrix
Content Type	Text
Resource Type	Article

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