Secured Cryptography cum Steganography Model with Large Message Embedding behind Colored Image by using Genetic Algorithm and OPA Process

This paper introduced a combined cryptography and steganography model to increase the security and the embedding capability of the standard colored images. Cryptography is used in this technique to provide more security. For this purpose we used a secret key (same for sender and receiver) for encryption and decryption process. Only sender and receiver can encrypt and decrypt the whole message by this secret key. For steganography we use genetic algorithm, optimal pixel adjustment process, integer to integer wavelet transform in frequency domain, inverse integer to integer wavelet transform. Genetic algorithm is applied here to achieve a mapping function of 8*8 matrix with minimum error difference between the input and the final image. In GA we use the block based mapping method because by using it we can preserve the input image properties. After it we employed the optimal pixel adjustment process for increasing the hiding capacity of the proposed algorithm in comparison to other existing algorithms. OPA process adjusts all the pixels of image optimally. MATLAB simulation results present that the hiding capacity and imperceptibility of image increase simultaneously. By using the optimization technique such as GA we can choose the best block size to reduce the computation cost and also increase the peak signal to noise ratio.

[1]  E Theodor,et al.  The origin of the species. , 1995, M.D. computing : computers in medical practice.

[2]  Sushil Jajodia,et al.  Steganalysis: the investigation of hidden information , 1998, 1998 IEEE Information Technology Conference, Information Environment for the Future (Cat. No.98EX228).

[3]  Nasir D. Memon,et al.  Analysis of LSB based image steganography techniques , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[4]  Christian Cachin,et al.  An information-theoretic model for steganography , 1998, Inf. Comput..

[5]  Jr. Allen B. Tucker,et al.  The Computer Science and Engineering Handbook , 1997 .

[6]  D. Artz,et al.  Digital steganography: hiding data within data , 2001 .

[7]  D. E. Goldberg,et al.  Genetic Algorithms in Search, Optimization & Machine Learning , 1989 .

[8]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[9]  Luca Cardelli,et al.  The Computer Science and Engineering Handbook , 1997 .

[10]  Thomas Bäck,et al.  Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .

[11]  R. A. Fisher,et al.  The Genetical Theory of Natural Selection , 1931 .

[12]  Robert I. Damper,et al.  Towards the evolutionary emergence of increasingly complex advantageous behaviours , 2000, Int. J. Syst. Sci..

[13]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[14]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[15]  Carlos D. Toledo Genetic algorithms for the numerical solution of variational problems without analytic trial functions , 2005 .