HIDING A MESSAGE IN MP3 USING LSB WITH 1, 2, 3 AND 4 BITS

International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.3, May 2016
DOI: 10.5121/ijcnc.2016.8305 67
HIDING A MESSAGE IN MP3 USING LSB WITH 1, 2,
3 AND 4 BITS
Alaa AbedulsalamAlarood1,2
,Azizah Abed Manaf1
, Mohammed J. Alhaddad2
and
Mohammed Salem Atoum3
1
Department of Computing, University Technology Malaysia, Johor Bahru.
2
Department of information Technology, King Abdulaziz University, Jeddah
3
Department of Computer Science, Irbid National University, Irbid
ABSTRACT
Steganography is the art of hiding information in ways that prevent the detection of hidden messages. This
paper presentsa new method which randomly selects position in MP3 file to hide a text secret messageby
using Least Significant Bit (LSB) technique. The text secret message isused in start and ends locations a
unique signature or key.The methodology focuses to embed one bit, two bits, three bitsor four bits from
secret message into MP3 file by using LSB techniques. The evaluation and performancemethods are based
on robustness (BER and correlation), Imperceptibility (PSNR) and hiding capacity (Ratio between Sizes of
text message and MP3 Cover) indicators.The experimental results show the new method is more security.
Moreover the contribution of this paper is the provision of a robustness-based classification of LSB
steganography models depending on their occurrence in the embedding position.
KEYWORDS
Steganography, LSB, mp3 data set, hiding a message
1. INTRODUCTION
Steganography is the art and science of hiding information by embedding messages within others,
seemingly harmless messages. Steganography means “covered writing” in Greek. As the goal of
steganography is to hide the presence of a message and create a covert channel, it can be seen as
the complement of cryptography, whose goal is to hide the content of a message [1].
Steganography basically aims at hiding communication between two parties from the attackers
[3]. Steganography operates by embedding a secret message which might be a copyright mark, or
a covert communication, or a serial number in a cover message such as a video film, an audio
recording, or computer code in such a way that it cannot be accessed by any wrong person during
data exchange.
The three types of Steganography include the first, Pure Steganography where there is no need for
the key. , Second Secret Key steganography and lastly, Public Key Steganography is based on the
concepts of public key cryptography. Public key steganography uses a public key and a private
key to secure the communication between the parties [20].
Steganography technique used in the data hiding process must have important properties in order
to secure data successfully. Some of these properties include robustness, imperceptibility and
capacity. These properties are explained below. Robustness means resistance to “blind”, non-
targeted modifications, or common image operations [6]. Imperceptibility is typically required for

68
secure covert communication. For example, if a steganography method uses the noise component
of digital images to embed a secret message, it should do so while not making statistically
significant changes to the noise in the carrier.Capacity or (Data Rate) refers to the amount of
information that can be hidden relative to the size of the cover message [21].
Figure 1. properties of steganography
2. STENOGRAPHIC METHODS
This section analyses the steganography which help understand the topic in a new perspective
Steganography methods can be classified mainly into six categories, although in some cases exact
classification is not possible [2].
• Substitution methods substitute redundant parts of a cover with a secret message (spatial
domain). A number of methods exist for hiding information in various media. These
methods range from LSB coding also known as bit plane or noise insertion
toolsmanipulation of image or compression algorithms to modification of image properties
such as luminance. Basic substitution systems try to encode secret information by
substituting insignificant parts of the cover by secret message bits; the receiver can extract
the information if he has knowledge of the positions where secret information has been
embedded. Since only minor modifications are made in the embedding process, the sender
assumes that they will not be noticed by a passive attacker.[14]
• Transform domain techniques embed secret information in a transform space of the signal
(frequency domain): It has been noted early in the development of stenographic systems
that embedding information in the frequency domain of a signal can be much more robust
than embedding rules operating in the time domain. Most robust stenographic systems
known today actually operate in some sort of transform domain.[15]
• Spread spectrum techniques: define spread spectrum techniques as "means of transmission
in which the signal occupies a bandwidth in excess of the minimum necessary to send the
information; the band spread is accomplished by means of a code which is independent of
Capacity
Imperceptibility Robustness

69
the data, and a synchronized reception with the code at the receiver is used for dispreading
and subsequent data recovery.[16]
• Statistical methods encode information by changing several statistical properties of a cover
and use hypothesis testing in the extraction process.
• Distortion techniques store information by signal distortion and measure the deviation from
the original cover in the decoding step.
• Cover generation methods encode information in the way a cover for secret communication
is created.
3. DATA SET GENERATION AND PREPARATION
The dataset that is used in this research are cover files and secret messages. The cover files are
MP3 files and the secret message is text. Most researchers who work in MP3 steganography used
their own file for testing, and did not use standard data set. However, the types of MP3 file that
are used have been generated from the standard dataset used in [17].
3.1 COVER DATASET
In the proposed Algorithm, the cover files are MP3 files. MP3 was created in 1993 by the
Fraunhofer Institute and since then, it has become the most used methods for audio compression.
The algorithm was standardized as MPEG-1 Layer III (ISO 11172-3). This algorithm achieves a
good data compression when using the knowledge of the limitations in the human hearing to
eliminate information without affecting the sound quality perception [18]. To generate MP3 file,
standard data set uses a program to convert each genre from wave file to MP3 file. Many
common programs are used to convert between different audio formats such as Free Make Audio
converter. However, there are five different bit rate encoding compression methods in MP3
compression: 320 kbps, 256 kbps, 196 kbps, 128 kbps and 96 kbps. The differences between bit
rate methods, encoding compression are impact of sound quality, where increasing the number of
bits per sample means increasing the quality of sound. The sampling frequencies for bit rate for
(320, 256 and 192 kbps) are 48 KHz and for 128 kbps is 44.1 KHz and for 96 kbps is 22.050 KHz
respectively. Table 1 shows MP3 standard data set generated to be implemented in this paper
[22].
From Table 1, it can be concluded that the size of a wave file is more than the size of MP3 files.
Furthermore, the different sizes between MP3 file depend on the time of music and the number of
bits per sample. If the quality is important, the size should be more.
Table 1. MP3 Dataset
Name of
genre
Size of file
(WAVE)
Size under
320kbps
MP3
Size under
256kbps
MP3
Size under
192kbps
MP3
Size under
128kbps
MP3
Size under
96kbps
MP3
Classical 14.7 6.67 5.33 4 2.66 2
Jazz 16.2 7.34 5.87 4.4 2.93 2.2
Country 18.7 8.48 6.78 5.08 3.39 2.54
R&B 19.4 8.81 7.05 5.29 3.52 2.64
Rap 20.1 9.14 7.31 5.48 3.65 2.74
Reggae 20.1 9.14 7.31 5.48 3.65 2.74

70
Pop 20.2 9.16 7.33 5.49 3.66 2.75
Rock 23 10.4 8.35 6.26 4.17 3.13
Blues 11.8 10.7 8.59 6.44 4.29 3.22
Hip-hop 27.5 12.4 9.98 7.48 4.99 3.74
Dance 31.3 14.2 11.3 8.53 5.68 4.26
Metal 32.6 14.8 11.8 8.88 5.92 4.44
3.2 SECRET MASSAGE
The secret message is text; there are six different sizes of secret massage 100 KB, 200 KB, 400
KB, 800 KB, 1 MB and 2 MB.
Table 2. Text Datasets used as a secret message
Name of Text Size Size byte
100.txt 100 KB 102,590 bytes
200.txt 200 KB 205,180 bytes
400.txt 400 KB 410,364 bytes
800.txt 800 KB 819,932 bytes
1Mb.txt 1 MB 1,049,704 bytes
2Mb.txt 2 MB 2,099,408 bytes
4. PROPOSED ALGORITHM
To make stego MP3 file by reading an MP3 audio file and text message file then, embed the text
file inside the audio MP3 to generate stego MP3 that contains a specific message.
4.1 PRE-PROCESSING FOR MP3 AND TEXT FILES
Will read the MP3 File and returns an output argument as the analog value of the audio samples,
properties of the MP3 file, sampling frequency, and number of bits. In addition, we remove the
header and timeframe.in parallel way read the text file, after that compare the size of MP3 file
with text file if I can embedded or not.

Figure
The parameters of the MP3 file will be measured and estimated to determine the size of data,
encoding and other parameters. The embedding is start from random location inside the audio
file. The random start location is calculated as the following equation:
Irand=ceil (rand*fix (Espace/2)) +
Where Espace is calculated as the
Espace=r-rb*cb/deg–200
Where, “r” is the number of samples in the MP3 file“rb*cb” is the size of text message file
“deg” is the number insertion bits“rand” is a function that generates random number from 0 to
1.This will generates a random sta
insertion will be located inside the MP3 file.
4.2 Digitizing for MP3 and Text file
To enable digital handling of the text file, all text data then converted to digital format. The Text
file is firstly converting to ASCII format, takes the string of the text data as input argument and
returns the ASCII code for each character. Below is an example of this function
>>double ('Hello')
ans = 72 101 108 108 111
The result of this function is in decimal format not hexadecimal, and no need to convert it to
hexadecimal format at old. Instead, it should be converted to binary directly. Each single
character is being converted separately to binary. The result of binar
Figure 1 Pre-Processing MP3 files
parameters. The embedding is start from random location inside the audio
file. The random start location is calculated as the following equation:
) +200
Where Espace is calculated as the following:
1.This will generates a random starting location of embedding where it ensures that, the end of
insertion will be located inside the MP3 file.
Digitizing for MP3 and Text file
s firstly converting to ASCII format, takes the string of the text data as input argument and
returns the ASCII code for each character. Below is an example of this function
ans = 72 101 108 108 111
character is being converted separately to binary. The result of binary conversion will be in a
71
parameters. The embedding is start from random location inside the audio
(1)
(2)
rting location of embedding where it ensures that, the end of
s firstly converting to ASCII format, takes the string of the text data as input argument and
y conversion will be in a

72
matrix of two-dimension format, as shown in the example bellow of the “Hello” word. The row
indicates the character, and the columns represent the binary code for the specific character.
>>dec2bin (‘ans’)
ans =
1001000
1100101
1101100
1101100
1101111
We used function to converts the decimal numbers to binary as the following equation where Bdi
is the binary digit index, and Ddi+1 is the decimal digit division result. And the “rem” is the
division remainder.
Bdi=rem (Ddi+1/2) (3)
The results will be a two dimensional matrix with size of Rx8 where the 8 is the number of bits
for ASCII character conversion to binary, and the R is the number of characters in the text file. R
is counting not only alphabetic characters, but also any ASCII symbol including the space and
carriage return.
4.3 Normalize MP3 and Text files
When the text file is processed and converted to binary, then the MP3 audio file should be
processed tool. The first step of audio file processing is to normalize it. As the third party function
that reads the MP3 file express it as analog value, then, each MP3 sample will have a value in the
interval [-1, +1] with float number format, By theory, the float number is an approximation in
digital system, and thus, any process over it will comprise an accumulated error. Therefore, to
deal with this analog value with minimal error, that’s limit approaches to zero, then, normalizing
it to higher value is required. The following equations illustrate how to normalize the analog
numbers of the audio MP3. Where the AiN is the ith normalized sample of the audio array A.
AiN=(Ai+1)*106
(4)
After normalized sample audio processing is to convert the normalized audio samples to binary
format. The conversion function is the same that has been used for the text file conversion that is
described before.
4.4 Build Stego-object
Once the audio is being normalized and converted to binary, and the text file has been converted
to ASCII then to binary, then, the data is ready to build the stego file starting by embedding the
binary that represents the text within the binary that represents the audio. If fact, because of the
embedding starts from random location within the MP3 file, the embedded message should be
bounded by its start and end locations. The start location follows start signature or key, and the
end location is just before end signature or key. Another issue is that, multi-bits insertion is
possible, so, the key should contain information about the number of insertion bits. The following
signatures are used at start of every message embedding:

73
Single bit insertion 10101010101010
Two bits insertion 01010101010101
Three bits insertion 10101010101010, 01010101010101
Four bits insertion 01010101010101, 10101010101010
The same signature is being used for start and end of embedding. So, the massage is being
bounded within the same signature that indicates start and end of the message, in addition to
number of insertion bits. The embedding is being done in terms of insertion. The insertion is a
method that is simply removes a bit or number of bits from the carrier data and inserts new bit or
bits from the message data.
The figure 2 bellow shows how to insert one bit, and two bits from the message to the carrier. The
insertion is being done in terms of least significant bit. From (least significant), its noticeable
effect of the actual digital value is negligible. So, the insertion will not highly affect the resulted
audio data with respect to the person who hears the MP3 audio file.
There are four insertion scenarios depending on the number of bits those are inserted within the
carrier, according to the developed system. Single bit insertion, two bits insertion, three bits
insertion, and four bits insertion is possible and those are selected with the input arguments of the
developed program. The figure above shows how to insert single bit, and two bits only. The
described process above is continued until all text data bits inserted within the digital carrier data
that represents the audio MP3 data.
Figure 3. the insert 1 bit, and 2 bits from the message to the carrier
Once the all-binary samples of text file were inserted and the process is completed, an inverse
process will be performed in the post-processing phase. The resulted digital array that represented
the stego MP3 file will be converted to decimal again in an inverse process of that described
above. Where above a decimal to binary conversion is being accomplished, but now, binary to
decimal will be performed. The following equation illustrates how to convert the binary data to
decimal.

74
Dd=∑bi*2i (5)
Where Dd is the decimal digit that is resulted after conversion, bi is the ith binary bit value, i is the
index of the binary bit. The “i” has values from 0 to 22. Hence, the maximum normalized decimal
number is 2x106
, that’s why the maximum number of i is 22.The resulted decimal data is
normalized according to the normalization process that is described above. Thus, de-
normalization is required to get the analog audio format again. The following equation is being
used for de-normalization.
Ai= (AiN*106
)-1 (6)
The latest step is finally to convert the stego audio data to an MP3 format file. The same toolbox
for MP3 format handling is also used; it contains an MP3 write function. It takes the number of
bits and MP3 encoding format to generate formal MP3 file. The same MP3 parameters those are
gotten when read of the original MP3 file are used to write the new stego MP3 file.
In figure 4The following flowchart that explain process of the model that start to read the text
and MP3 file and then Normalize MP3 file and convert the text file to ASCII format, and then
Embeddedbits within the MP3 file, after finish that we reverse the process to restores the MP3
file as normal MP3.
Figure 4. Process for embedding Text to MP3 fil

75
5. EXPERIMENTAL RESULTS
The Peak Signal-to-Noise Ratio (PSNR) is the ratio between a signal's maximum power and the
power of the signal's noise. Engineers commonly use the PSNR to measure the quality of
reconstructed signals that have been compressed. Signals can have a wide dynamic range, so
PSNR is usually expressed in decibels as show Comparisonsbetween embedded different bits in
figure 7. In statistics, the Mean Squared Error (MSE) of an estimator is one of many ways to
quantify the difference between values implied by an estimator and the true values of the quantity
being estimated. MSE is a risk function, corresponding to the expected value of the squared error
loss or quadratic loss. MSE measures the average of the squares of the "errors." The error is the
amount by which the value implied by the estimator differs from the quantity to be estimated, as
show Comparisonsbetween embedded different bits in figure 6. [19].
Table 3. PSNR and MSE values of ten audio files at 200 kb text message s
Name of genre PSNR MSE No. of Embedding
Classical 75.4490 0.0019 7714000
Jazz 63.0154 0.0325 8494000
Country 63.1514 0.0315 9805000
R&B 63.7896 0.0272 10195000
Rap 58.7419 0.0869 10573000
Reggae 60.8632 0.0533 10571000
Pop 65.4141 0.0187 10596000
Rock 65.4814 0.0184 12068000
Blues 66.9008 0.0133 12423000
Dance 64.1514 0.0175 13486000
Hip-Hop 66.2314 0.0168 13926000
Metal 63.4814 0.0135 14499000
In Error! Reference source not found.5 shows the signal structure of the audio file Rap.MP3 at
before embedding. By using MP3 audio with 128kbps and the size of MP3 3.65 MB (3,836,190
bytes) and the genre Rap. Also use 200 KB the secret Message.
Figure 5. the signal level comparisons between a MP3 carrier file before and after the LSB with size 3.65
MB Text 200 KB
Before embed message
After embed message

76
Table 4. PSNR and MSE values of ten audio files at 200 kb text message when embedded 1 bit and
embedded 2 bits
Name of genre embedded 1 bit embedded 2 bits
PSNR MSE No. of
Embedding
PSNR MSE No. of
Embedding
Classical 78.1266 0.0010 7714 77.6796 0.0011 7714
Jazz 63.4224 0.0296 8494 63.4224 0.0296 8494
Country 63.5267 0.0289 9805 63.5267 0.0289 9805
R&B 64.1845 0.0248 10194 64.1845 0.0248 10194
Rap 59.1376 0.0793 10572 59.1376 0.0793 10572
Reggae 61.2687 0.0486 10571 61.2687 0.0486 10571
Pop 66.1688 0.0157 10595 65.7593 0.0173 10595
Rock 65.8772 0.0168 12067 65.8772 0.0168 12067
Blues 67.3400 0.0120 12422 67.3400 0.0120 12422
Dance 67.0223 0.0129 16443 65.2804 0.0193 16443
Hip-Hop 60.1148 0.0633 14423 58.8159 0.0854 14423
Metal 68.1388 0.0100 17114 66.8664 0.0134 17114
Table 5 PSNR and MSE values of ten audio files at 200 kb text message when embedded 3 bits and 4 bits
Name of genre embedded 3 bits embedded 4 bits
PSNR MSE No. of
Embedding
PSNR MSE No. of
Embedding
Classical 77.6796 0.0014 7714 77.2308 0.0012 7714
Jazz 63.4224 0.0267 8494 64.3006 0.0242 8494
Country 63.5267 0.0262 9805 64.3789 0.0237 9805
R&B 64.1845 0.0225 10194 65.0483 0.0203 10194
Rap 59.1376 0.0719 10572 59.9930 0.0651 10572
Reggae 61.2687 0.0439 10571 62.1421 0.0397 10571
Pop 65.7593 0.0142 10595 67.0086 0.0129 10595
Rock 65.8772 0.0152 12067 66.7580 0.0137 12067
Blues 67.3400 0.0108 12422 67.9554 0.0110 12422
Dance 65.2804 0.0193 16443 65.2817 0.0193 16443
Hip-Hop 58.8159 0.0854 14423 58.8168 0.0854 14423
Metal 66.8664 0.0134 17114 66.8681 0.0134 17114

Figure 6. Comparisons between different
Figure 7. Comparisons between different results for Mean Squared Error (MSE)
6.CONCLUSIONS
This paper has explored and reviewed MP3 audio steganography, particularly with respect to
MP3 files after compression. LSB in time domain has been developed to use randomly position
from cover file to hide the secret message by using 1
meeting the three most important audio steganography requirements, which are imperceptibility,
capacity, and robustness. Any technique tries to enhance the capacity or robustness should
0
0.02
0.04
0.06
0.08
0.1
0.12
0
10
20
30
40
50
60
70
80
omparisons between different results for Mean Squared Error (MSE)
Comparisons between different results for Mean Squared Error (MSE)
explored and reviewed MP3 audio steganography, particularly with respect to
from cover file to hide the secret message by using 1, 2, 3 and 4 bits. The new Model
MSE 1 bit
MSE 2 bits
MSE 3bits
MSE 4 bits
PSNR 1 bit
PSNR 2 bits
PSNR 3bits
PSNR 4 bits
77
Mean Squared Error (MSE)
Comparisons between different results for Mean Squared Error (MSE)
explored and reviewed MP3 audio steganography, particularly with respect to
Model aims at
MSE 1 bit
MSE 2 bits
MSE 3bits
MSE 4 bits
PSNR 1 bit
PSNR 2 bits
PSNR 3bits
PSNR 4 bits

78
preserve imperceptibility. A new method is increased the capacity and robustness as well as
improved the imperceptibility. In this paper, we concentrate model that has been built, achieved
hiding the data in Audio file, by keeping the accuracy of the audio file high, even though, one
mange to discover the secret message, still extracting the message is challenging.
6. ACKNOWLEDGEMENTS
This Project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz
University, Jeddah, under grant no. (G-481-611-37). The authors, therefore, acknowledge with
thanks DSR for technical and financial support
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AUTHORS
Mr.Alaaalarood He still continues his Ph.D. in UniversityTechnology Malaysia (UTM)
Faculty of computingand Information Technology. He is Lecturer of king abed alaziz
university, Department of Computing and Information Technology.His research interests
are Information Security,steganalysis, steganography, Artificial Intelligence ANN, and
Computer Graphics.
Prof. Azizah Abdul Manaf, Professor of Computer Science, Deputy Dean Academic
Advanced Informatics School (UTM AIS) UniversitiTeknologi Malaysia (UTM) her
research interests are Image Processing, Multimedia Security, Computer Forensics.
Mohammed J. Alhaddad Associate Professor in Faculty of Information Technology at
King Abdulaziz University. Visiting Associate Professor at University Teknologi
Malaysia, His research interests are: network Security, Artificial Intelligence, Robots,
Brain Computer Interface BCI.
Mohammed Salem Atoum is assistant professor in Irbid National University. His
research interests,Steganography, Watermarking, data hiding,cryptography,Information
Security.

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