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Feature based steganalysis using wavelet decomposition and magnitude statistics

Publication Type : Conference Paper

Thematic Areas : TIFAC-CORE in Cyber Security

Publisher : ACE 2010 - 2010 International Conference on Advances in Computer Engineering

Source : ACE 2010 - 2010 International Conference on Advances in Computer Engineering, Bangalore, p.298-300 (2010)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-77956137084&partnerID=40&md5=ae590e69c76f51c005e5cbaa280ea551

ISBN : 9780769540580

Keywords : Cover-image, Embedding algorithms, Feature-based, Hidden messages, High resolution image, Image features, Image processing, Steganalysis, Steganography, SVM, SVM classifiers, Wavelet decomposition

Campus : Coimbatore

School : Centre for Cybersecurity Systems and Networks, School of Engineering

Center : TIFAC CORE in Cyber Security

Department : Computer Science, cyber Security

Year : 2010

Abstract : Steganography is broadly used to embed information in high resolution images, since it can contain adequate information within the small portion of cover image. Steganalysis is the procedure of finding the occurrence of hidden message in an image. This paper compares the efficiency of two embedding algorithms using the image features that are consistent over a wide range of cover images, but are distributed by the presence of embedded data. Image features were extracted after wavelet decomposition of the given image. These features were then given to a SVM classifier to identify the stego content. © 2010 IEEE.

Cite this Research Publication : Dr. Gireesh K. T., Jithin, R., and Shankar, D. D., “Feature based steganalysis using wavelet decomposition and magnitude statistics”, in ACE 2010 - 2010 International Conference on Advances in Computer Engineering, Bangalore, 2010, pp. 298-300.

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