EST

Call for paper
April Edition 2017

International Journal of Applied Information Systems solicits high quality original research papers for the
March 15, 2017
April 2017 Edition of the journal.
The last date of research paper submission is
March 15, 2017
SUBMIT YOUR PAPER

Number 3

Cellular Automata and Chaotic Maps for Speech Signal Encryption

User Rating: 0 / 5

Star InactiveStar InactiveStar InactiveStar InactiveStar Inactive
 

PrintEmail

journal image
  • International Journal of Applied Information Systems
  • Foundation of Computer Science (FCS), NY, USA
  • Volume 9 - Number 3
  • Year of Publication:
  • Authors: Eman Hato
  • 10.5120/ijais15-451377
 Download
658

Export

  • Eman Hato 2015. Cellular Automata and Chaotic Maps for Speech Signal Encryption. International Journal of Applied Information Systems. 9, 3 (June 2015), 9-16. DOI=http://dx.doi.org/10.5120/ijais451377 
  • @article{10.5120/ijais2017451568,
author = {Eman Hato},
title = {Cellular Automata and Chaotic Maps for Speech Signal Encryption},
journal = {International Journal of Applied Information Systems},
issue_date = {June 2015},
volume = {9},
number = {},
month = {June},
year = {2015},
issn = {},
pages = {9-16},
numpages = {},
url = {/archives/volume9/number3/760-1377-1},
doi = { 10.5120/ijais15-451377},
publisher = { xA9 2015 by IJAIS Journal},
address = {}
}

  • %1 451377
%A Eman Hato
%T Cellular Automata and Chaotic Maps for Speech Signal Encryption
%J International Journal of Applied Information Systems
%@ 
%V 9
%N 
%P 9-16
%D 2015
%I  xA9 2015 by IJAIS Journal

Abstract

Character Recognition has been one of the most intensive research during the last few decades because of its potential applications. However, most existing classifiers used in recognizing online handwritten characters suffer from poor feature selection and slow convergence which affect training time and recognition accuracy. Hence, this paper focused on integrating an optimization (genetic algorithm) into modified backpropagation neural network to enhance the performance of character recognition. This paper proposed a methodology that is based on extraction of features using stroke number, invariant moments, projection and zoning. Genetic algorithm was use as feature selection to optimize the subset of the character for classification. A Modified Genetic Algorithm (MGA) was modified to reduce character recognition errors using fitness function and genetic operators. However, an integration of optimization algorithm (modified genetic algorithm) into an existing modified backpropagation (MOBP) learning algorithm was employed as classifier. For further enhancement of classifier, three classifiers (C1, C2 and C3) were formulated from MGA-MOBP model and evaluated using training time and correct recognition accuracy. C3 performed better than C1 and C2 in terms of convergence rate, correct recognition accuracy and feature selection (its ability to remove irrelevant features of character images). The results of the developed system achieved a false recognition of 0.56% and 99.44% overall recognition accuracy compared with existing models.

References

  1. Srinivasan A. and Arul Selvan P. , "A Review of Analog Audio Scrambling Methods for Residual Intelligibility", Innovative Systems Design and Engineering, Vol. 3, No. 7, PP. 22-39, 2012.
  2. Musheer Ahmad, Bashir Alam and Omar Farooq, "Chaos Based Mixed Keystream Generation for Voice Data Encryption", International Journal on Cryptography and Information Security (IJCIS), Vol. 2, No. 1, PP. 39-48, 2012.
  3. Musheer Ahmad, Bashir Alam and Omar Farooq, "Chaos Based Mixed Keystream Generation for Voice Data Encryption", International Journal on Cryptography and Information Security (IJCIS), Vol. 2, No. 1, PP. 39-48, 2012.
  4. Fasel Qadir , M. A. Peer, K. A. Khan, "Digital Image Scrambling Based on Two Dimensional Cellular Automata", I. J. Computer Network and information Security, Vol. 2, PP. 36-41, 2013.
  5. Alia Madain, Abdel Latif Abu Dalhoum, Hazem Hiary•Alfonso Ortega, Manuel AlfonsecaAlia Madain " Audio Scrambling Technique Based on Cellular Automata", Multimedia Tools and Applications, Vol. 71, Issue 3, PP. 1803-1822 , 2014.
  6. Ljupco Kocarev and Shiguo Lian (Eds. ), "Chaos-Based Cryptography Theory, Algorithms and Applications, Studies in Computational Intelligence", Springer Vol. 354, 2011.
  7. Swati Rastogi and Sanjeev Thakur," Security Analysis of Multimedia Data Encryption Technique Using Piecewise Linear Chaotic Maps", International Journal on Recent and Innovation Trends in Computing and Communication Vol. 1, Issue 5, PP. 458 - 461, 2013.
  8. Hui Lu, Xiaoteng Wang, Zongming Fei, and Meikang Qiu, "The Effects of Using Chaotic Map on Improving the Performance of Multiobjective Evolutionary Algorithms" , Hindawi Publishing Corporation Mathematical Problems in Engineering , Article ID 924652,16 pages, 2014.
  9. N. K. Pareek , Vinod Patidar , K. K. Sud, "Cryptography using Multiple One-Dimensional Chaotic Maps", Communications in Nonlinear Science and Numerical Simulation, Vol. 10, PP. 715–723, 2005.
  10. Mosa E. , Messiha N. W. , Zahran O. and Abd El-Samie F. E. , " Chaotic Encryption of Speech Signals", Int. J Speech Technol. , Vol. 14, PP. 285-296, 2011.

Keywords

Speech encryption, Cellular automata, Game of life, Chaotic maps, Residual intelligibility.

Index Terms

Computer Science
Information Sciences