• DocumentCode
    1950924
  • Title

    Finding Optimal LSB Substitution Using Ant Colony Optimization Algorithm

  • Author

    Hsu, Ching-Sheng ; Tu, Shu-Fen

  • Author_Institution
    Dept. of Inf. Manage., Ming Chuan Univ., Taipei, Taiwan
  • fYear
    2010
  • fDate
    26-28 Feb. 2010
  • Firstpage
    293
  • Lastpage
    297
  • Abstract
    The Least Significant Bit (LSB) Substitution is a kind of information hiding method. The secret message is embedded into the last r bits of a cover image to get away from the notice of hackers. The security and stego-image quality are two main issues of the LSB substitution method. Therefore, some researchers propose an LSB substitution matrix to address these two issues. Finding an optimal LSB substitution matrix can be seen as a problem of combinatorial optimization. There are 2r! feasible solutions, hence the search space grows notably when r increases. Consequently, an efficient method to construct the matrix is necessary. In this paper, we apply the Ant Colony Optimization Algorithm to construct an optimal LSB substitution matrix. The experimental results show that ACO can find optimal LSB substitution matrix efficiently and improve the qualities of the stego-images.
  • Keywords
    combinatorial mathematics; image processing; matrix algebra; message authentication; optimisation; steganography; ant colony optimization algorithm; combinatorial optimization; information hiding; least significant bit; optimal LSB substitution matrix; secret message; security; stego-image quality; Ant colony optimization; Biological cells; Computer hacking; Cryptography; Information management; Matrices; Particle swarm optimization; Pixel; Protection; Steganography; Ant Colony Optimization; LSB substitution matrix; Least siginificatn bit substituion; image hiding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Software and Networks, 2010. ICCSN '10. Second International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5726-7
  • Electronic_ISBN
    978-1-4244-5727-4
  • Type

    conf

  • DOI
    10.1109/ICCSN.2010.61
  • Filename
    5437677