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--The art of hiding secret message.
By
K.SHARATH REDDY
ECE Department
 STEGANOGRAPHY
 AUDIO STEGANOGRAPHY
 AUDIO STEGANOGRAPHIC SYSTEM
 AUDIO STEGANOGRAPHY TECHNIQUES
 ADVANTAGES AND DISADVANTAGES
 APPLICATIONS
 STEGAN-O-GRAPHY
“The goal of steganography is to hide messages
in such a way that no one apart from the
intended recipient even knows that a message
has been sent.”
 This can be achieve by concealing the
existence of information within seemingly
harmless carriers or cover.
 It can be understand by the following figure.
Embedding secret messages into digital
sound is known as Audio Steganography.
Audio Steganography methods can embed
messages in WAV, AU, and even MP3 sound
files.
The properties of the human auditory
system (HAS) are exploited in the process of
audio Steganography
To embed data secretly onto digital audio
file there are few techniques introduced :
LSB Coding
Phase Coding
Parity Coding
Spread Spectrum
 The message 'HEY' is encoded in a 16-bit CD
quality sample using the LSB method.
 Here the secret information is ‘HEY’ and the
cover file is audio file. HEY is to be embedded
inside the audio file. First the secret
information ‘HEY’ and the audio file are
converted into bit stream.
 The least significant column of the audio file is
replaced by the bit stream of secret information
‘HEY’. The resulting file after embedding secret
information ‘HEY’ is called Stego-file.
The phase coding method works by substituting
the phase of an initial audio segment with a
reference phase that represents the data. The
procedure for phase coding is as follows:
 The original sound sequence is broken into a
series of N short segments.
 A discrete Fourier transform (DFT) is applied to
each segment, to break create a matrix of the
phase and magnitude.
The phase difference between each adjacent
segment is calculated.
For segment S0, the first segment, an
artificial absolute phase p0 is created.
For all other segments, new phase frames
are created.
 The new phase and original magnitude are
combined to get a new segment, Sn.
 Finally, the new segments are concatenated to
create the encoded output
 One of the prior works in audio data hiding
technique is parity coding technique.
 Instead of breaking a signal down into
individual samples, the parity coding method
breaks a signal down into separate regions of
samples
 Encode each bit from the secret message in a
sample region's parity bit
 If the parity bit of a selected region does not
match the secret bit to be encoded,
 This process flips the LSB of one of the
samples in the region. Thus, the sender has
more of a choice in encoding the secret bit, and
the signal can be changed in a more
unobtrusive fashion.
 The basic spread spectrum (SS) method attempts to spread
secret information across the frequency spectrum of the
audio signal.
 This system is similar to a system which uses an
implementation of the LSB that spreads the message bits
randomly over the entire sound file.
 Unlike LSB coding, the Spread Spectrum method spreads
the secret information over the frequency spectrum of the
sound file using a code which is independent of the actual
signal.
 As a result, the final signal occupies a bandwidth which is
more than what is actually required for transmission.
Potential capability to hide the existence of
confidential data
Hardness of detecting the hidden (i.e.,
embedded) data
Strengthening of the secrecy of the
encrypted data
The confidentiality of information is
maintained by the algorithms, and if the
algorithms are known then this technique is
of no use.
 Password leakage may occur and it leads to
the unauthorized access of data.
Confidential communication and secret data
storing
Protection of data alteration
Access control system for digital content
distribution
Media Database systems
Alleged use by intelligence services
Steganography, though is still a fairly new idea.
There are constant advancements in the computer
field, suggesting advancements in the field of
steganography as well.
In the future, it is hoped that the technique of
Steganalysis will advance such that it will become
much easier to detect even small messages within
an audio file.
The intent of this presentation was to cover some
of the more common methods of data hiding
using widespread file formats and easily available
tools as an introduction ,to the primary concepts
of steganography. These discussions should serve
as a starting point to the exploration of more
complex steganographic techniques involving, for
example, the use of network packets and unused
hard disk space as cover medium, or the more
complex methodologies used on our audio files.
 S. William, Cryptography and Network Security:
Principles and Practice, 2nd edition, Prentice-Hall,
Inc., 1999 pp 23-50
 Bloom. A. et al., 2008. Digital watermarking and
Steganography. 2nd edition
 A. Westfield. "F5 - A Steganographic Algorithm:
High Capacity Despite Better Steganalysis", Lecture
Notes in Computer Science, vol. 2137, pp. 289-302,
2001.
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Audio steganography

  • 1. --The art of hiding secret message. By K.SHARATH REDDY ECE Department
  • 2.  STEGANOGRAPHY  AUDIO STEGANOGRAPHY  AUDIO STEGANOGRAPHIC SYSTEM  AUDIO STEGANOGRAPHY TECHNIQUES  ADVANTAGES AND DISADVANTAGES  APPLICATIONS
  • 4. “The goal of steganography is to hide messages in such a way that no one apart from the intended recipient even knows that a message has been sent.”  This can be achieve by concealing the existence of information within seemingly harmless carriers or cover.  It can be understand by the following figure.
  • 5. Embedding secret messages into digital sound is known as Audio Steganography. Audio Steganography methods can embed messages in WAV, AU, and even MP3 sound files. The properties of the human auditory system (HAS) are exploited in the process of audio Steganography
  • 6.
  • 7. To embed data secretly onto digital audio file there are few techniques introduced : LSB Coding Phase Coding Parity Coding Spread Spectrum
  • 8.
  • 9.  The message 'HEY' is encoded in a 16-bit CD quality sample using the LSB method.  Here the secret information is ‘HEY’ and the cover file is audio file. HEY is to be embedded inside the audio file. First the secret information ‘HEY’ and the audio file are converted into bit stream.  The least significant column of the audio file is replaced by the bit stream of secret information ‘HEY’. The resulting file after embedding secret information ‘HEY’ is called Stego-file.
  • 10.
  • 11. The phase coding method works by substituting the phase of an initial audio segment with a reference phase that represents the data. The procedure for phase coding is as follows:  The original sound sequence is broken into a series of N short segments.  A discrete Fourier transform (DFT) is applied to each segment, to break create a matrix of the phase and magnitude.
  • 12. The phase difference between each adjacent segment is calculated. For segment S0, the first segment, an artificial absolute phase p0 is created. For all other segments, new phase frames are created.
  • 13.  The new phase and original magnitude are combined to get a new segment, Sn.  Finally, the new segments are concatenated to create the encoded output
  • 14.  One of the prior works in audio data hiding technique is parity coding technique.  Instead of breaking a signal down into individual samples, the parity coding method breaks a signal down into separate regions of samples  Encode each bit from the secret message in a sample region's parity bit
  • 15.  If the parity bit of a selected region does not match the secret bit to be encoded,  This process flips the LSB of one of the samples in the region. Thus, the sender has more of a choice in encoding the secret bit, and the signal can be changed in a more unobtrusive fashion.
  • 16.
  • 17.  The basic spread spectrum (SS) method attempts to spread secret information across the frequency spectrum of the audio signal.  This system is similar to a system which uses an implementation of the LSB that spreads the message bits randomly over the entire sound file.  Unlike LSB coding, the Spread Spectrum method spreads the secret information over the frequency spectrum of the sound file using a code which is independent of the actual signal.  As a result, the final signal occupies a bandwidth which is more than what is actually required for transmission.
  • 18.
  • 19. Potential capability to hide the existence of confidential data Hardness of detecting the hidden (i.e., embedded) data Strengthening of the secrecy of the encrypted data
  • 20. The confidentiality of information is maintained by the algorithms, and if the algorithms are known then this technique is of no use.  Password leakage may occur and it leads to the unauthorized access of data.
  • 21. Confidential communication and secret data storing Protection of data alteration Access control system for digital content distribution Media Database systems Alleged use by intelligence services
  • 22. Steganography, though is still a fairly new idea. There are constant advancements in the computer field, suggesting advancements in the field of steganography as well. In the future, it is hoped that the technique of Steganalysis will advance such that it will become much easier to detect even small messages within an audio file.
  • 23. The intent of this presentation was to cover some of the more common methods of data hiding using widespread file formats and easily available tools as an introduction ,to the primary concepts of steganography. These discussions should serve as a starting point to the exploration of more complex steganographic techniques involving, for example, the use of network packets and unused hard disk space as cover medium, or the more complex methodologies used on our audio files.
  • 24.  S. William, Cryptography and Network Security: Principles and Practice, 2nd edition, Prentice-Hall, Inc., 1999 pp 23-50  Bloom. A. et al., 2008. Digital watermarking and Steganography. 2nd edition  A. Westfield. "F5 - A Steganographic Algorithm: High Capacity Despite Better Steganalysis", Lecture Notes in Computer Science, vol. 2137, pp. 289-302, 2001.
  • 25.