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Steganalysis of LSB Embedded Images Using Gray Level Co-Occurrence Matrix
H.B.Kekre, A.A.Athawale, Sayli Anand Patki
Pages - 36 - 45     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 5   Issue - 1    |    Publication Date - March / April 2011  Table of Contents
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KEYWORDS
Steganography, Steganalysis, LSB Embedding, GLCM, Distance Measures
ABSTRACT
This paper proposes a steganalysis technique for both grayscale and color images. It uses the feature vectors derived from gray level co-occurrence matrix (GLCM) in spatial domain, which is sensitive to data embedding process. This GLCM matrix is derived from an image. Several combinations of diagonal elements of GLCM are considered as features. There is difference between the features of stego and non-stego images and this characteristic is used for steganalysis. Distance measures like Absolute distance, Euclidean distance and Normalized Euclidean distance are used for classification. Experimental results demonstrate that the proposed scheme outperforms the existing steganalysis techniques in attacking LSB steganographic schemes applied to spatial domain.
CITED BY (13)  
1 Luo, D., Sun, M., & Huang, J. (2016). Audio Post-processing Detection Based on Amplitude Co-occurrence Vector Feature.
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Dr. H.B.Kekre
Mukesh Patel School of Technology Management & Engineering - India
Mr. A.A.Athawale
Mukesh Patel School of Technology Management & Engineering - India
Miss Sayli Anand Patki
K.J.Somiaya Institute of Engineering and Information Technology - India
sayli_patki@rediffmail.com