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Optimizing Image Steganography using Particle Swarm Optimization Algorithm

by Rafael Lima De Carvalho, Warley Gramacho Da Silva, Ary Henrique Oliveira De Morais
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 164 - Number 7
Year of Publication: 2017
Authors: Rafael Lima De Carvalho, Warley Gramacho Da Silva, Ary Henrique Oliveira De Morais
10.5120/ijca2017913686

Rafael Lima De Carvalho, Warley Gramacho Da Silva, Ary Henrique Oliveira De Morais . Optimizing Image Steganography using Particle Swarm Optimization Algorithm. International Journal of Computer Applications. 164, 7 ( Apr 2017), 1-5. DOI=10.5120/ijca2017913686

@article{ 10.5120/ijca2017913686,
author = { Rafael Lima De Carvalho, Warley Gramacho Da Silva, Ary Henrique Oliveira De Morais },
title = { Optimizing Image Steganography using Particle Swarm Optimization Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 164 },
number = { 7 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume164/number7/27492-2017913686/ },
doi = { 10.5120/ijca2017913686 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:10:38.063121+05:30
%A Rafael Lima De Carvalho
%A Warley Gramacho Da Silva
%A Ary Henrique Oliveira De Morais
%T Optimizing Image Steganography using Particle Swarm Optimization Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 164
%N 7
%P 1-5
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image Steganography is the computing field of hiding information from a source into a target image in a way that it becomes almost imperceptible from one’s eyes. Despite the high capacity of hiding information, the usual Least Significant Bit (LSB) techniques could be easily discovered. In order to hide information in more significant bits, the target image should be optimized. In this paper, it is proposed an optimization solution based on the Standard Particle Swarm Optimization 2011 (PSO), which has been compared with a previous Genetic Algorithm-based approach showing promising results. Specifically, it is shown an adaptation in the solution in order to keep the essence of PSO while remaining message hosted bits unchanged.

References
  1. C. Blum and D. Merkle. Swarm Intelligence: Introduction and Applications. Natural Computing Series. Springer Berlin Heidelberg, 2008.
  2. Maurice Clerc. What is a Difficult Problem? ISTE, 2010.
  3. Maurice Clerc. Standard particle swarm optimisation, 2012. 15 pages.
  4. Gangeshawar and James Attri. Optimizing image steganography using genetic algorithm. International Journal of Engineering Trends and Technology (IJETT), 24(1):32–38, 2015.
  5. S. Katzenbeisser and F.A.P. Petitcolas. Information Hiding Techniques for Steganography and Digital Watermarking. Artech House computer security series. Artech House, 2000.
  6. J. Kennedy and R. Eberhart. Particle swarm optimization. In Neural Networks, 1995. Proceedings., IEEE International Conference on, volume 4, pages 1942–1948 vol.4, Nov 1995.
  7. G. Kipper. Investigator’s Guide to Steganography. CRC Press, 2003.
  8. Oliver Kramer. Genetic Algorithm Essentials, volume 679 of Studies in Computational Intelligence. Springer, 2017.
  9. Melanie Mitchell. An Introduction to Genetic Algorithms. Complex Adaptive Systems. The MIT Press, first printing. edition, 1996.
  10. Sachin Mungmode, R.R. Sedamkar, and Niranjan Kulkarni. A modified high frequency adaptive security approach using steganography for region selection based on threshold value. Procedia Computer Science, 79:912 – 921, 2016.
  11. Y.G. Petalas, K.E. Parsopoulos, and M.N. Vrahatis. Memetic particle swarm optimization. Annals of Operations Research, 156(1):99–127, 2007.
  12. Frank Y. Shih. Digital Watermarking and Steganography: Fundamentals and Techniques. CRC Press, Inc., Boca Raton, FL, USA, 1st edition, 2007.
  13. M. Zambrano-Bigiarini, M. Clerc, and R. Rojas. Standard particle swarm optimisation 2011 at cec-2013: A baseline for future pso improvements. In Evolutionary Computation (CEC), 2013 IEEE Congress on, pages 2337–2344, June 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Image Steganography Particle Swarm Optimization Genetic Algorithm Image Processing Optimization

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