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Implementation of Radial Basis Function Neural Network for Image Steganalysis
Sambasiva Rao Baragada, S. Ramakrishna, M.S. Rao, S. Purushothaman
Pages - 12 - 22     |    Revised - 15-02-2008     |    Published - 30-02-2008
Volume - 2   Issue - 1    |    Publication Date - February 2008  Table of Contents
Steganography, carrier image, covert image
Steganographic tools and techniques are becoming more potential and widespread. Illegal use of steganography poses serious challenges to the law enforcement agencies. Limited work has been carried out on supervised steganalysis using neural network as a classifier. We present a combined method of identifying the presence of covert information in a carrier image using fisher’s linear discriminant (FLD) function followed by the radial basis function (RBF). Experiments show promising results when compared to the existing supervised steganalysis methods, but arranging the retrieved information is still a challenging problem.
CITED BY (14)  
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9 Awad, M., & Occupied, P. (2010). Optimization RBFNNs Parameters using Genetic Algorithms: Applied on Function Approximation Full text.
10 Bhowmik, M. K., Bhattacharjee, D., Nasipuri, M., Basu, D. K., & Kundu, M. (2010). A Parallel Framework for Multilayer Perceptron for Human Face Recognition. arXiv preprint arXiv:1007.0627.
11 Tirdad, K. (2010). Developing pseudo random number generator based on neural networks and neurofuzzy systems.
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13 Baragada, S. R., Ramakrishna, S., Rao, M. S., & Purushothaman, S. (2009). Polynomial Discriminant Radial Basis Function for Steganalysis. International Journal of Computer Science and Network Security, IJCSNS, 9(2), 209-218.
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Mr. Sambasiva Rao Baragada
Mr. S. Ramakrishna
Mr. M.S. Rao, S. Purushothaman