## Summary

### BibTeX

@MISC{Baragada_summary,

author = {Sambasiva Rao Baragada and S. Ramakrishna and M. S. Rao and S. Purushothaman},

title = {Summary},

year = {}

}

### OpenURL

### Abstract

Steganalysis plays an important role in identifying unacceptable information transmitted through internet communication system. In the process of steganalysis many untoward incidents can be avoided. Many techniques have been proposed and new techniques are tried with different combinations to maximize the efficiency of retrieving hidden information. We have proposed a combination of polynomial vector with Fisher’s discriminant function using the information of bitplane and radial basis neural network (PVDRBF). Each set of pixel is preprocessed to obtain interpolated pixels using PDV. This is further trained by Fisher’s discriminant method that transforms once again into 2-dimensional vector. A processing of training the RBF is adopted to obtain set of final weights. During implementation, the final weights are used to classify the presence of hidden information. Key words:

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Citation Context ...erns of higher dimensions (more than two dimensions) can be seen on a two dimensional graph. The mapping operation can be linear or non-linear. R.A. Fisher developed a linear classification algorithm =-=[18]-=- and a method for constructing a classifier on the optimal discriminant plane, with minimum distance criterion for multi-class classification with small number of patterns [19]. The method of consider... |

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Citation Context ...or, Interpolation, bitplane, Steganalysis, Carrier image, Covert image. 1. Introduction Steganalysis is the process of identifying the presence of hidden information in a text, image, audio, or video =-=[1,2,3]-=-. Most of the present literature on steganalysis follows either a parametric model [10, 11, 12] or a blind model [4, 5, 6, 7, 8, 9]. A generic steganalysis method that can attack steganography blindly... |

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Citation Context ...or, Interpolation, bitplane, Steganalysis, Carrier image, Covert image. 1. Introduction Steganalysis is the process of identifying the presence of hidden information in a text, image, audio, or video =-=[1,2,3]-=-. Most of the present literature on steganalysis follows either a parametric model [10, 11, 12] or a blind model [4, 5, 6, 7, 8, 9]. A generic steganalysis method that can attack steganography blindly... |

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Citation Context ...or, Interpolation, bitplane, Steganalysis, Carrier image, Covert image. 1. Introduction Steganalysis is the process of identifying the presence of hidden information in a text, image, audio, or video =-=[1,2,3]-=-. Most of the present literature on steganalysis follows either a parametric model [10, 11, 12] or a blind model [4, 5, 6, 7, 8, 9]. A generic steganalysis method that can attack steganography blindly... |

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Citation Context ...ganography blindly, detect hidden data without knowing embedding methods, will be more useful in practical applications. A framework for steganalysis based on supervised learning has been designed in =-=[13]-=-. The framework was further developed and tested. A mere significant work has been carried out on supervised steganalysis, using neural networks as a classifier [14, 15]. Fishers’ linear discriminant ... |

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Citation Context ...dentifying the presence of hidden information in a text, image, audio, or video [1,2,3]. Most of the present literature on steganalysis follows either a parametric model [10, 11, 12] or a blind model =-=[4, 5, 6, 7, 8, 9]-=-. A generic steganalysis method that can attack steganography blindly, detect hidden data without knowing embedding methods, will be more useful in practical applications. A framework for steganalysis... |

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Citation Context ...dentifying the presence of hidden information in a text, image, audio, or video [1,2,3]. Most of the present literature on steganalysis follows either a parametric model [10, 11, 12] or a blind model =-=[4, 5, 6, 7, 8, 9]-=-. A generic steganalysis method that can attack steganography blindly, detect hidden data without knowing embedding methods, will be more useful in practical applications. A framework for steganalysis... |

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Citation Context ...eganalysis is the process of identifying the presence of hidden information in a text, image, audio, or video [1,2,3]. Most of the present literature on steganalysis follows either a parametric model =-=[10, 11, 12]-=- or a blind model [4, 5, 6, 7, 8, 9]. A generic steganalysis method that can attack steganography blindly, detect hidden data without knowing embedding methods, will be more useful in practical applic... |

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Citation Context ... is the discriminant vector ϕ2. In Eq.(12) and Eq. (14), SW should be non-singular. The SW matrix should be non-singular, even for a more general discriminating analysis and multi-orthonormal vectors =-=[31, 32, 33]-=-. If the determinant of SW is zero, then singular value decomposition (SVD) on SW has to be done. On using SVD [34, 35], SW is decomposed into three matrices U, W and V. The matrices U and W are unita... |

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Citation Context ...dentifying the presence of hidden information in a text, image, audio, or video [1,2,3]. Most of the present literature on steganalysis follows either a parametric model [10, 11, 12] or a blind model =-=[4, 5, 6, 7, 8, 9]-=-. A generic steganalysis method that can attack steganography blindly, detect hidden data without knowing embedding methods, will be more useful in practical applications. A framework for steganalysis... |

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Citation Context ...ear mapping is used to map an n-dimensional vector space ℜ n onto a two dimensional space. Some of the linear mapping algorithms are principal component mapping [22], generalized declustering mapping =-=[23, 24, 25, 26]-=-, least squared error mapping [27] and projection pursuit mapping [28]. In this work, the generalized declustering optimal discriminant plane is used. The mapping of the original pattern ‘X’ onto a ne... |

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Citation Context ... carried out on supervised steganalysis, using neural networks as a classifier [14, 15]. Fishers’ linear discriminant function (FLD) as a classifier has shown impressive results for steganalysis work =-=[37]-=-. We extend the present neural network based steganalytic work by combining a polynomial interpolated fisher’s discriminant method with the radial basis function neural network function. 2. Methodolog... |

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Citation Context ...ear mapping is used to map an n-dimensional vector space ℜ n onto a two dimensional space. Some of the linear mapping algorithms are principal component mapping [22], generalized declustering mapping =-=[23, 24, 25, 26]-=-, least squared error mapping [27] and projection pursuit mapping [28]. In this work, the generalized declustering optimal discriminant plane is used. The mapping of the original pattern ‘X’ onto a ne... |

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Citation Context ...ctor space ℜ n onto a two dimensional space. Some of the linear mapping algorithms are principal component mapping [22], generalized declustering mapping [23, 24, 25, 26], least squared error mapping =-=[27]-=- and projection pursuit mapping [28]. In this work, the generalized declustering optimal discriminant plane is used. The mapping of the original pattern ‘X’ onto a new vector ‘Y’ on a plane is done by... |

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Citation Context ... is the discriminant vector ϕ2. In Eq.(12) and Eq. (14), SW should be non-singular. The SW matrix should be non-singular, even for a more general discriminating analysis and multi-orthonormal vectors =-=[31, 32, 33]-=-. If the determinant of SW is zero, then singular value decomposition (SVD) on SW has to be done. On using SVD [34, 35], SW is decomposed into three matrices U, W and V. The matrices U and W are unita... |

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Citation Context ...es (or increases) monotonically with distance from a central point. The centre, the distance scale, and the precise shape of the radial function are parameters of the model, all fixed if it is linear =-=[36]-=-. A typical radial function is the Gaussian which, in the case of a scalar input, is h(x)=exp((-(x-c) 2 )/(r 2 )) (18) Its parameters are its centre c and its radius r. RBF networks have traditionally... |

2 |
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1 |
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Citation Context ...pattern set by a polynomial set obtained by outer producting the given pattern. It can also be described as, given some points, the aim is to find a polynomial which goes exactly through these points =-=[16, 17]-=-. Polynomial v) Linear plus NL2 (NL5) The pre-processed input vector is a 6-dimensional vector. (5) vi) Linear plus NL3 (NL6) (6) The pre-processed input vector is a 9-dimensional vector. In Eq. (1) t... |

1 |
Polynomial Discriminant Radial Basis Function for Steganalysis
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Citation Context ...nificant work has been carried out on supervised steganalysis, using neural networks as a classifier [14, 15, 26-32]. Polynomial processed vector has shown impressive results for steganalysis work in =-=[18]-=-. We tried to present another combination of polynomial vector discriminant with back propagation algorithm neural network. (a) (b) Fig. 1 a) Flowchart for training, b) flowchart for testing Manuscrip... |

1 | Kurugollu F,”SVD Based Universal Spatial Domain Image Steganalysis - Gul - 2010 |

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Citation Context ...has been noticed that the present literature on steganalysis is broadly categorized as supervised learning model, parametric model [10, 11, 12], blind model [4, 5, 6, 7, 8, 9, 19-25] and hybrid model =-=[29]-=-. A generic steganalysis method that can attack steganography Sun college of Engineering and Technology Nagerkoil, INDIA blindly, detect hidden data without knowing embedding methods, will be more use... |

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