01-06-2012, 12:58 PM
COMPUTER SECURITY & CRYPTOGRAPHY
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Data Hiding in Audio Signa:
Abstract
Information hiding technique is a new kind of secret communication technology. The majority of today’s information hiding systems uses multimedia objects like audio.
Embedding secret messages in digital sound is usually a more difficult process. Varieties of
techniques for embedding information in digital audio have been established. In this paper we
will attend the general principles of hiding secret information using audio technology, and an
overview of functions and techniques.
Keywords: Audio data hiding, parity coding, phase coding, spread spectrum, echo hiding, LSB.
1. Introduction
The fast improvement of the Internet and the digital information revolution caused major
changes in the overall culture. Flexible and simple-to-use software and decreasing prices of
digital devices (e.g. portable CD and mp3players, DVD players, CD and DVD recorders,
laptops, PDAs) have made it feasible for consumers from all over the world to create, edit and
exchange multimedia data. Broadband Internet connections almost an errorless transmission
of data helps people to distribute large multimedia files and make identical digital copies of
them. In modern communication system Data Hiding is most essential for Network Security
issue. Sending sensitive messages and files over the Internet are transmitted in an unsecured
form but everyone has got something to keep in secret. Audio data hiding method is one of
the most effective ways to protect your privacy.
2. Overview
General principles of data hiding technology, as well as terminology adopted at the First
International Workshop on Information Hiding, Cambridge, U.K. [1] are illustrated in Figure
1. A data message is hidden within a cover signal (object) in the block called embeddor using
a stego key, which is a secret set of parameters of a known hiding algorithm. The output of
the embeddor is called stego signal (object). After transmission, recording, and other signal
processing which may contaminate and bend the stego signal, the embedded message is
retrieved using the appropriate stego key in the block called extractor [2].
Figure 1. Block diagram of data hiding and retrieval.
A number of different cover objects (signals) can be used to carry hidden messages. Data
hiding in audio signals exploits imperfection of human auditory system known as audio
masking. In presence of a loud signal (masker), another weaker signal may be inaudible,
depending on spectral and temporal characteristics of both masked signal and masker [3]
Masking models are extensively studied for perceptual compression of audio signals [2] In
the case of perceptual compression the quantization noise is hidden below the masking
threshold, while in a data hiding application the embedded signal is hidden there. Data hiding
in audio signals is especially challenging, because the human auditory system operates over a
wide dynamic range. The human auditory system perceives over a range of power greater
than one billion to one and a range of frequencies greater than one thousand to one.
Sensitivity to additive random noise is also acute. The perturbations in a sound file can be
detected as low as one part in ten million (80 dB below ambient level).However, there are
some “holes” available. While the human auditory system has a large dynamic range, it has a
fairly small differential range. As a result, loud sounds tend to mask out quiet sounds.
Additionally, the human auditory system is unable to perceive absolute phase, only relative
phase. Finally, there are some environmental distortions so common as to be ignored by the
listener in most cases [4]. Now we will discuss many of these methods of audio data hiding
technology.
3. Previous works
This section presents some common methods used for hiding secret information in audio.
Many software implementations of these methods are available on the Web and are listed in
the relatives section. Some of the latter methods require previous knowledge of signal
processing techniques, Fourier analysis, and other areas of high level mathematics. When
developing a data-hiding method for audio, one of the first considerations is the likely
environments the sound signal will travel between encoding and decoding. There are two
main areas of modification which we will consider. First, the storage environment, or digital
representation of the signal that will be used, and second the transmission pathway the signal
might travel [4].
3.1. Parity coding
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 and encodes 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, the 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 [5]. Figure 2, shows the parity coding procedure.
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3.2. Phase Coding
The phase coding method works by substituting the phase of an initial audio segment with
a reference phase that represents the data. The phase of subsequent segments is adjusted in
order to preserve the relative phase between segments. Phase coding, when it can be used, is
one of the most effective coding methods in terms of the signal-to perceived noise ratio.
When the phase relation between each frequency component is dramatically changed,
noticeable phase dispersion will occur. However, as long as the modification of the phase is
sufficiently small (sufficiently small depends on the observer; professionals in broadcast radio
can detect modifications that are imperceivable to an average observer), an inaudible coding
can be achieved [4]. . Phase coding relies on the fact that the phase components of sound are
not as perceptible to the human ear as noise is. Rather than introducing perturbations, the
technique encodes the message bits as phase shifts in the phase spectrum of a digital signal,
achieving an inaudible encoding in terms of signal-to-perceived noise ratio [5].
Figure 2. Parity Coding Procedure.
Phase coding is explained in the following procedure:
a. The original sound signal is broken up into smaller segments whose lengths equal
the size of the message to be encoded.
b. A Discrete Fourier Transform (DFT) is applied to each segment to create a matrix
of the phases and Fourier transform magnitudes.
c. Phase differences between adjacent segments are calculated.
d. Phase shifts between consecutive segments are easily detected. In other words, the
absolute phases of the segments can be changed but the relative phase differences
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Vol. 2, No. 2, June 2009
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between adjacent segments must be preserved. Therefore the secret message is
only inserted in the phase vector of the first signal segment as follows:
e. A new phase matrix is created using the new phase of the first segment and
the original phase differences.
f. Using the new phase matrix and original magnitude matrix, the sound signal
is reconstructed by applying the inverse DFT and then concatenating the
sound segments back together.
To extract the secret message from the sound file, the receiver must know the
segment length. The receiver can then use the DFT to get the phases and extract the
information (consider Figure 3 for phase cosing procedure).
Figure 3. The signals before and after Phase coding procedure.