NDLI: Image Steganalysis Based on Statistical Moments of Wavelet Subband Histogram of Images with Least Significant Bit planes

Content Provider	IEEE Xplore Digital Library
Author	Mehrabi, Mohammad Ali Aghaeinia, Hassan Abolghasemi, Mojtaba
Copyright Year	2008
Abstract	This paper proposed a new image Steganalysis scheme based on statistical moments of histogram of multi-level wavelet subbands in frequency domain. These wavelet subbands derived from an image that has some of least significant bits of the grey level test image and some of its most significant bit planes are removed. Then we decompose the image using three-level Haar discrete wavelet transform (DWT) into 13 subbands (here the image itself is considered as the LL0 subband). The Fourier transform of each subband histogram, is calculated. The first three statistical moments of each subband histogram are selected to form a 39-dimensional feature vector for Steganalysis. Support Vector Machines (SVM) classifier is then used to discriminate between stego-images and innocent images. We experiment our proposed scheme on LSB, Cox and QIM data hiding method. Experimental results show that the proposed method improves the detection rate especially for LSB steganography.
Starting Page	768
Ending Page	772
File Size	566496
Page Count	5
File Format	PDF
ISBN	9780769531199
DOI	10.1109/CISP.2008.639
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet domain Fourier transforms Histogram Bit plane Discrete wavelet transforms Frequency domain analysis Support vector machines Wavelet Histograms Steganography Steganalysis Support vector machine classification Data encapsulation Testing
Content Type	Text
Resource Type	Article

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