Audio Stego

(Journal of Security Engineering), 6 3 2009 6

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Secure Data Transfer through Audio Signal

Debnath Bhattacharyya1), Poulami Dutta2), Tai-hoon Kim3)

Abstract

In this paper we propose the LSB technique for secure data transfer. Secret information can be hidden

inside all sorts of cover information: text, images, audio, video and more. Embedding secret messages in

digital sound is usually a more difficult process. Varieties of techniques for embedding information in

digital audio have been established. These are parity coding, phase coding, spread spectrum, echo hiding,

LSB. Least significant bits (LSB) insertion is one of the simplest approaches to embedding information in

audio file.

Keywords : LSB technique, watermarking, data hiding, parity coding, embedded information

1. Introduction

Currently the fast improvement of the Internet and the digital information revolution caused major changes in

the overall culture. In modern communication system Data Hiding is most essential for Network Security issue.

The internet has also encouraged a number of audio applications like internet telephony, voice query and

assistance on the net and voice activated web sites. Music is another subject of interest worldwide and reaches

its audience as audio files or internet radio broadcasts (apart from conventional radio and television). Audiotraffic on the internet is increasing at a high rate. Therefore, choosing audio as a cover media is quiteobvious for data hiding. Popular audio formats on the internet are the WAV (Windows Audio Visual), AIFF

(Audio Interchange File Format), log scale 8 bit m law and MP3 (Motion Picture Experts Group Layer III). Data rates supported vary from 8 kbps to 44.1 kbps. Audio hiding techniques rely on the weakness of the

human auditory system (HAS).

Hiding information inside audio is a popular technique now a day. Audio data hiding can be used any time

you want to hide data. There are many reasons to hide data but most important is to prevent unauthorized

persons from becoming aware of the existence of a message. Data hiding in the least significant bits (LSBs) of

Received(January 18, 2009), Review request(January 19, 2009), Review Result(1st:February 10, 2009, 2nd:February 28, 2009)Accepted(June 30, 2009)1Computer Science and Engineering Heritage Institute of Technology Kolkata, India

email: [email protected] Science and Engineering Heritage Institute of Technology Kolkata, India

email: [email protected](Corresponding Author) Professor, Department of Multimedia Engineering , Hannam University, 306-791.

email: [email protected]


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audio samples in the time domain is one of the simplest algorithms with very high data rate of additional

Information.

In this paper we will present general principles of data hiding basic terminology, and an overview of

applications and techniques. In particular we will consider data hiding within audio signals, basic requirements

and the state of the art techniques. We will propose a novel technique with several variations. The proposed

method is characterized by perfect transparency, robustness, high bit rate, low processing load, and, particularly,

high security.

2. 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 isthe 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].

2.1 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].

2.2 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 dramaticallychanged, noticeable phase dispersion will occur. However, as long as the modification of the phase is


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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]. 2.3 Spread Spectrum

In a normal communication channel, it is often desirable to concentrate the information in as narrow a

region of the frequency spectrum as possible in order to conserve available bandwidth and to reduce power.

The basic spread spectrum technique, on the other hand, is designed to encode a stream of information by

spreading the encoded data across as much of the frequency spectrum as possible. This allows the signal

reception, even if there is interference on some frequencies. While there are many variations on spread

spectrum communication, we concentrated on Direct Sequence Spread Spectrum encoding (DSSS). The DSSS

method spreads the signal by multiplying it by a chip, a maximal length pseudorandom sequence modulated at

a known rate. Since the host signals are in discrete time format, we can use the sampling rate as the chiprate for coding. The result is that the most difficult problem in DSSS receiving, that of establishing the correct

starts and ends of the chip quanta for phase locking purposes, is taken care of by the discrete nature of the

signal. Consequently, a much higher chip rate, and therefore a higher associated data rate, is possible. Without

this, a variety of signal locking algorithms may be used, but these are computationally expensive [4].

2.4 Echo Hiding

In echo hiding, information is embedded in a sound file by introducing an echo into the discrete signal.

Like the spread spectrum method, it too provides advantages in that it allows for a high data transmission rate

and provides superior robustness when compared to the noise inducing methods. If only one echo was produced

from the original signal, only one bit of information could be encoded. Therefore, the original signal is broken

down into blocks before the encoding process begins. Once the encoding process is completed, the blocks are

concatenated back together to create the final signal [5].

3. Proposed work and Analysis

Here we will discuss the disadvantages of the previous procedure and how those are different with present

method. There are two main disadvantages associated with the use of methods like parity coding. The human


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ear is very sensitive and can often detect even the slightest bit of noise introduced into a sound file, although

the parity coding method does come much closer to making the introduced noise inaudible. Another problem is

robustness. One disadvantage associated with phase coding is a low data transmission rate due to the fact that

the secret message is encoded in the first signal segment only. Phase coding method is used when only a

small amount of data needs to be considered.

Least significant bit (LSB) coding is the simplest way to embed information in a digital audio file. By

substituting the least significant bit of each sampling point with a binary message, LSB coding allows for a

large amount of data to be encoded. Among many different data hiding techniques proposed to embed secret

message within audio file, the LSB data hiding technique is one of the simplest methods for inserting data into

digital signals in noise free environments, which merely embeds secret message bits in a subset of the LSBplanes of the audio stream.

The method of LSB technique:

Receives the audio file in the form of Hex code and converted in to bit pattern.Each character in the message is converted in bit pattern.Replaces the LSB bit from audio with LSB bit from character in the message [11].

Proposed Audio data hiding is a method of hiding the message in the audio file formats. The proposed LSB

audio data hiding method was tested on a large set of songs from different music styles. The hiding operation

will be done on the basis of bit wise message hiding concept.

To hide a secret message into an audio file we are using following steps.

1. Select an audio file.

2. Converting the audio file into hexadecimal coded file.

3. Enter the secret information

4. Convert the secret message into equivalent ASCII

5. Convert each segment of the hexadecimal value of audio file into binary

6. Convert each ASCII of hiding data into binary

7. Encoding two binary data into the LSB part of the audio file

8. Hide message in audio file.


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[Fig. 1] Hiding data in WAV file

Here we used a .wav file as an audio file and converting into binary. After converting into binary this

method is very similar to hiding message in the pixels of a bitmap. This hiding method provides an easy way

of implementation of mechanism when compared with other audio data hiding method.

The main two features of this system are

1) Size of file will not changed after hiding data in audio file.

2) The sound variations cannot be determined by comparing previous and new file.

Here we 1st looked at a Wave file in a HEX editor. Hex editor applications the data of the audio file is

represented as hexadecimal values grouped in 4 groups of 4 bytes and one group of 16 ASCII characters. We

can see it in [Fig 2].

[Fig. 2] Hexadecimal code value of audio file.

Then we converting hexadecimal value to binary value. From [fig 3]. we can see the binary value of each

hex code.

[Fig. 3] Binary conversion of hex code.


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Here we proposed a method which is called zig zag lsb method. Where the binary value of the secret

message is inserted into the last bit of audio data but in zigzag basis.

Now suppose for example our secret message is A whose binary value is 10000011 .Using this method we

can hide the message A into the audio file . When the character A, whose binary value equals 10000011, is

inserted, the result we can see from [Fig 4]. and [Fig 5].

[Fig. 4] 1st group of hex code and secret data

In this case, only three bits needed to be changed to insert the character successfully. On average, only half

of the bits in an audio will need to be modified to hide a secret message using the maximal cover size. The

resulting changes that are made to the least significant bits are too small to be recognized by the human eye,so the message is effectively hidden.

[Fig. 5] Attaching secret bit in audio.

4. Conclusion

In this paper we have introduced a robust method of imperceptible audio data hiding. This system is to

provide a good, efficient method for hiding the data from hackers and sent to the destination in a safe manner.

This proposed system will not change the size of the file even after encoding and also suitable for any type of

audio file format. Thus we conclude that audio data hiding techniques can be used for a number of purposes

other than covert communication or deniable data storage, information tracing and finger printing, tamper

detection. As the sky is not limit so is not for the development. Man is now pushing away its own boundaries

to make every thought possible. So similarly these operations described above can be further modified as it is

in the world of Information Technology. After designing any operation every developer has a thought in his


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mind that he could develop it by adding more features to it.

References

[1] B. Pfitzmann, Information Hiding Terminology, First International Workshop on Information Hiding, May

30 June 1, 1996, Cambridge, UK, pp. 347 350. [2] Rade Petrovi, Kanaan Jemili, Joseph M. Winograd, Ilija Stojanovi, Eric Metois, DATA HIDING WITHIN

AUDIO SIGNALS, June 15, 1999, MIT Media Lab, Series: Electronics and Energetics vol. 12, No.2,

pp.103 122. http://pubs.media.mit.edu/?section=docdetail&id=211474&collection=Media+Lab&filtercollection =Media+Lab

[3] J. Johnston and K. Brandenburg, "Wideband Coding Perceptual Consideration for Speech and

Music".Advances in Speech Signal Processing, S. Furoi and M. Sondhi, Eds. New York: Marcel Dekker,

1992.

[4] W. Bender, W. Butera, D. Gruhl, R. Hwang, F. J. Paiz, S. Pogreb, Techniques for data hiding, IBM

Systems Journal, Volume 39 , Issue 3 4, July 2000, pp. 547 568.[5] Samir Kumar Bandyopadhyay, Debnath Bhattacharyya, Poulami Das, Debashis Ganguly and Swarnendu

Mukherjee, A tutorial review on Steganography, International Conference on Contemporary Computing

(IC3 2008), Noida, India, August 7 9, 2008, pp. 105 114. [6] Steve Czerwinski, Richard Fromm, Todd Hodes, Digital Music Distribution and Audio Watermarking.

http:// reference.kfupm.edu.sa/content/d/i/digital_music_distribution_and_audio_wat_1045219.pdf

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[7] Robert Krenn, Steganography and steganalysis, An Article, January 2004.

http://www.krenn.nl/univ/cry/steg/article.pdf

[8] Francesco Queirolo, Steganography in Images, Final Communications Report.

http://eric.purpletree.org/file/Steganography%20In%20Images.pdf

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Steganography, Springer, Vol. 3710/2005, pp. 15 29.[10] LoboGuerrero, A., Marques, F., Lienard, P.B.J., Enhanced audio data hiding synchronization using non

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International Journal of Database Theory and Application, Vol. 2, No. 2, June 2009


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Authors

Debnath Bhattacharyya

2004 : Allahabad Agricultural Institute, A Deemed University, Allahabad, M.Sc (IT)

2008 : West Bengal University of Technology, Kolkata, M.Tech in Computer Science and

Engineering

Research Interests : Biometric Authentication, Pattern Recognition, Security and medical

Imaging.

Based on

author's request,

Photo was not

displayed

Poulami Dutta

Computer Science and Engineering Heritage Institute of Technology Kolkata, India

Research Interests : Biometric Authentication, Pattern Recognition, medical Imaging.

Tai-hoon Kim

B.S., M.S., and Ph.D in Electricity, Electronics and Computer Engineering, Sungkyunkwan

University

2002 ~ 2004 : Senior Researcher, Korea Information Security Agency.

2004 ~ 2006 : Secretary, Defense Security Command.

2006 ~ 2007 : Research Professor, Ewha Woman's University.

2007 ~ Present : Professor, Hannam University.

Research interests : Security Engineering, SCADA Security.

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