• DocumentCode
    607694
  • Title

    A performance comparision about hiding methods for steganalysed audio files through chi-square and artificial neural networks

  • Author

    Durdu, Akif ; Ozcerit, A.T.

  • Author_Institution
    Bilgisayar Muhendisligi, Sakarya Univ., Sakarya, Turkey
  • fYear
    2013
  • fDate
    24-26 April 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this study, there has been carried a performance comparison on random and sequential hidden data of audio wav files by using the chi-square test and PNN with steganography technique that allows resolution of package. During performance of applied steganography method, it is assumed that hiding algorithm is known. It has been developed an analysis method for hidden objects created by using LSB steganography technique. LSB data hiding method that the hidden data embedded into last bits, has been strengthened by holding a performance comparison analysis both as random and sequential type about steganography algorithms. Lastly results has been optimized as real as possible by training of PNN neural network.
  • Keywords
    audio coding; learning (artificial intelligence); neural nets; steganography; LSB data hiding method; LSB steganography technique; PNN neural network; analysis method; applied steganography method; artificial neural networks; audio wav files; chi-square test; hidden objects; hiding algorithm; hiding methods; package resolution; performance comparison analysis; random hidden data; sequential hidden data; steganalysed audio files; steganography algorithms; training; Algorithm design and analysis; Conferences; Histograms; MATLAB; Neural networks; Streaming media; Digital Audio; Least Significant Bit (LSB); Probably Neural Network (PNN); Steganalysis; Steganography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2013 21st
  • Conference_Location
    Haspolat
  • Print_ISBN
    978-1-4673-5562-9
  • Electronic_ISBN
    978-1-4673-5561-2
  • Type

    conf

  • DOI
    10.1109/SIU.2013.6531355
  • Filename
    6531355