Steganalysis Using a Composite Set of Transform Domain Features and Ensemble Classifier

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In this paper, generic as well as analytic steganalysis method is used to detect the presence of hidden image and also the tool used to embed the secret image in the cover image. Identifying the type of embedding algorithm might lead to extraction of the hidden image. A new set of features including Noise features, Zernike moments, Moments of Characteristic Function (MOCF), Colour, Fourier Descriptors are extracted independently and are given to different classifiers including Minimum Distance Classifier (MDC), Least Squares Support Vector Machine (LS SVM), OSU SVM  etc and their steganalytic performance is analysed. In order to improve their performance, ensemble classifier is used. The performance of the Steganalyzer is also analyzed with different number of training, testing subjects. The experimental results demonstrated that the proposed method can effectively identify digital images from their tampered or stego versions and can also successfully classify the steganographic algorithm with which the secret was embedded into the cover image.
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Steganalysis; Noise Features; Zernike Moments; Moments of Characteristic Function; Colour Features; Fourier Descriptors

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Siwei Lyu, Hany Farid, Steganalysis Using Higher-Order Image Statistics, IEEE transactions on Information Forensics and Security, vol. 1, n. 1, pp. 111-119, March 2006.

Sos Agaian, Hong Cai, Color Wavelet Based Universal Blind Steganalysis, International TICSP workshop on Spectral methods and Multirate Signal processing(SMMSP 2004), Vienna, Austria, (pp 183-189Sep 11-12, 2004).

Guorong Xuan, Yun Q. Shi, Jianjiong Gao, Dekun Zou, Chengyun Yang, Zhenping Zhang, Peiqi Chai, Chunhua Chen, Wen Chen, Steganalysis Based on Multiple Features Formed by Statistical Moments of Wavelet Characteristic Functions, Lecture notes in computer science: 7th International Workshop on Information Hiding in 2005.

Wen-Nung Lie, Guo-Shiang Lin, A Feature-Based Classification Technique For Blind Image Steganalysis, IEEE Transcations On Multimedia, vol.7, n.6, pp.Dec 2005.

Tomáš Pevný, Patrick Bas, Jessica Fridrich, Steganalysis by Subtractive Pixel Adjacency Matrix, IEEE transactions on Information and security, vol.5 n.5, pp. 215-224, June 2010.

Lu Zhiwu, Lu Xiaoqing, Wavelet Statistics for Steganalysis Using Image Noise, High Technology Letters, vol. 12. pp.1-4, 2006.

M. Abolghasemi, H. Aghaeinia, K. Faez, Data Hiding Detection Based on DWT and Zernike Moments, SETIT 2007 International Conference: Sciences of Electronic, Technologies of Information and Telecommunications March 25-29, 2007.

A. Swaminathan, Min Wu, Noise Features On Image Tampering Detection and Steganalysis, IEEE International Conference on Image processing 2007.

Tu-Thach Quacha, Fernando P´erez-Gonz´alezb, Gregory L. Heileman, Model-based steganalysis using invariant features, Spieei09, 2009.

T.H. Manjula Devi, H.S. Manjunatha Reddy, K.B.Raja Venugopal, L.M.Patnaik, Detecting Original image Using Histogram, DFT and SVM, ACEEE International Journal on Signal & Image Processing, Vol.1, n.1, pp. 17 – 21, May 2009.

Natarajan Meghanathan, Lopamudra Nayak, Steganalysis Algorithms For Detecting The Hidden Information In Image, Audio And Video Cover Media, International Journal of Network Security & Its Application (IJNSA), Vol.2, No.1, pp.43-55, January 2010.

Diyanat, Farhat, Ghaemmaghami, Image steganalysis based on SVD and noise estimation: Improve sensitivity to spatial LSB embedding families, TENCON 2011 - 2011 IEEE Region 10 Conference, Nov.2011.

Shunquan Tan, Bin Li, Targeted Steganalysis of Edge Adaptive Image Steganography Based on LSB Matching Revisited Using B-Spline Fitting, IEEE Signal processing, vol.19, n.6, pp.336-339, June 2012.


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