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International Journal of Computer Applications (0975 – 8887)
Volume 70– No.18, May 2013
29
Hiding Data in Text using ASCII MappingTechnology (AMT)
Souvik Bhattacharyya Department of CSE University Institute of
Technology, The University of Burdwan
West Bengal,India
Pabak Indu Department of CSE University Institute of
Technology, The University of Burdwan
West Bengal,India
Gautam Sanyal Department of CSE National Institute of
Technology,Durgapur West Bengal,India
ABSTRACT
In current digitized world humane race is facing a great
revolution over Internet technologies, as a result every single
information needs to be transmitted through a communication
network. This results a different level of attack over these
information. This attacks, misuse or unauthorized access of
this information are greatest concern of today‟s world.
Steganography means “covered or hidden writing”,
originated from Greek language, an ancient art of protecting
information. Considerable amount of work has been carried
out by different researchers on Steganography. In this paper
the authors propose a novel text steganography method based
on ASCII Mapping Technology (AMT) on English language
producing stego text with which is visibly indistinguishable
from the original cover text. There is an extra level of security
which is achieved through a derived quantum gate. This
solution is independent of the nature of the data to be hidden
and produces a stego text with minimum degradation and
applicable for other India languages also. Quality of the stego
text is analyzed by tradeoff between no of bits used for
mapping. Efficiency of the proposed method is illustrated by
exhaustive experimental results and comparisons.
General Terms
Steganography, Cover Text, Stego Text, Quantum gates, C-
NOT gate, SWAP gate, NOT gate.
Keywords
AMT (ASCII Mapping Technology), CS gate, CSN gate, POS
file, Jaro-Winkler Distance.
1. INTRODUCTION
In current world the main concern of the information
transmission over a communication network is the protection
of data from unauthorized user. To deal with this problem,
there exists several information hiding mechanisms like,
Steganography, Cryptography, Digital watermarking etc. The
first two techniques provides protection on data where as the
third one gives the authentication over the data using some tag
or labeling on some objects like text, audio, video, image [1].
As the goal of steganography is to hide the presence of a
message and to create a covert channel, it can be seen as the
complement of cryptography, whose goal is to hide the
content of a message. The message is hidden in another media
such that the transmitted data will be meaningful and
innocuous looking to everyone. In summary it can be said
cryptography attempting to conceal the content of the secret
message, steganography conceals the very existence of that [2,
3]. Steganalysis is the art of detecting any hidden message on
the communication channel. If the existence of the hidden
message is revealed, the goal of steganography is defeated. A
famous illustration of modern day steganography is Simmons‟
Prisoners‟ Problem [4]. An assumption can be made based
on this model is that if both the sender and receiver
share some common secret information then the
corresponding steganography protocol is known as then
the secret key steganography where as pure
steganography means that there is none prior information
shared by sender and receiver. If the public key of the
receiver is known to the sender, the steganographic
protocol is called public key steganography [3], [5] and
[6]. For a more thorough knowledge of steganography
methodology the reader is advised to see [7-8]. Figure 1
show below the framework of modern day steganography.
Figure 1: Frame work of modern day Steganography
A message is embedded in a Cover-Object with the help of a
embedding algorithm and a key, which is shared by both
sender and receiver, thus resulting an identical Stego-Object
which is transmitted through a communication channel and
the extraction algorithm extracts the secret message from the
Stego-Media with the help of the key
Although all digital file formats can be used for
steganography, but the image and audio files are more suitable
because of their high degree of redundancy [21]. Figure 2
below shows the different categories of file formats that can
be used for steganography techniques.
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Figure 2: Types of Steganography
Among them Image Steganography is most popular of the lot.
In this technique secret message is embedded into an image as
a noise, whose detection is nearly impossible to an human eye
[9, 10, 11]. Audio Steganography embeds the message into a
cover audio file as noise at a frequency beyond human hearing
range [12-13]. A video is nothing but a collection of moving
images, with some audio associated. Video Steganography
can be achieved by the same methods used previously.
Linguistic Steganography or Text Steganography is a major,
and perhaps most difficult kind of this category. The Text
Steganography is a method of using written natural language
to conceal secret message as defined by Chapman et al [14].
Some Steganographic model with high security features has
been presented in [15-18].
In steganography two aspects are usually addressed. First, the
cover-media and stego media should appear identical under all
possible statistical attacks. Second, the embedding process
should not degrade the media fidelity, that is, the difference
between the stego media and the cover-media should be
imperceptible to human perceptual system.
This paper has been organized as following sections:- Section
II discusses about some of the related works done based on
text steganography. Section III describes proposed text
steganography method. Section IV describes the
Mathematical formulation of the processes. Solution
methodology has been provided in section V. Section VI
describes different algorithms .Section VII contains the
analysis of the results. Section VIII compares the proposed
method with other existing and Section IX draws the
conclusion.
2. REVIEW OF RELATED WORKS IN
TEXT STEGANOGRAPHY
Depending upon the method used, the text steganography can
be classified into three categories as shown in Figure 3.
Figure 3 : Classification of Text Steganography
2.1 Format-Based
Format-Based methods use and change the formatting of the
cover-text to hide data. This method does not bring any
change to any sentence or to any word. Thus the „value‟ of the
cover-text is unharmed. A format-based text steganography
method is open space method. In this method extra white
spaces are added into the text to hide information. A single
space represents “0” while two consecutive spaces are
represented as “1”. By line and word shifting [19],
manipulating the white spaces between words and paragraph
[20] this method can also be achieved. In line shifting method,
vertical alignments of some lines of the text are shifted to
create a unique hidden shape to embed message in it [21].
2.2 Random and Statistical Generation
Random and statistical generation methods are used to
generate cover-text automatically according to the statistical
properties of language. These methods use example grammars
to produce cover-text in a certain natural language. A
probabilistic context-free grammar (PCFG) is a commonly
used language model where each transformation rule of a
context-free grammar has a probability associated with it
[22].The quality of the generated stego-message depends
directly on the quality of the grammars used. Another
approach to this type of method is to generate words having
same statistical properties like word length and letter
frequency of a word in the original message. The words
generated are often without of any lexical value.
2.3 Linguistic Method
The Linguistic method [23] considers the linguistic properties
of the text to modify it. To hide information the method uses
the linguistic structure of the message. Syntactic method is a
linguistic steganography method where some punctuation sign
like comma (,) and full-stop (.) are placed in proper places in
the document to embed data.
2.4 Changing Alphabet Letter Pattern
(CALP)
CALP is a new method for text steganography presented in
[24, 25]. In this method, considering the structure of English
alphabets each one or two bit of the binary sequence of the
secret message has been mapped through some little structural
modification of some of the alphabets of the cover text .This
approach uses the idea of structural and feature changing of
the cover carrier which is not visibly distinguishable from the
original to the human beings and may be modified for other
India language also. This solution is independent of the nature
of the data to be hidden and produces a stego text with
minimum degradation.
2.5 Other Methods
Except the above mentioned methods, there are some other
methods proposed for text steganography, such as feature
coding, text steganography by specific characters in words,
abbreviations etc. [26] or by changing words spelling [27].
Some other methods like Text Steganography by Inter-word
Spacing and Inter paragraph Spacing Approach [20] or Text
Steganography by Using Letter Points and Extensions [28].
Text Steganography by Word Mapping Method (WMM) [29]
are also exist.
3. PROPOSED METHOD OF TEXT
STEGANOGRAPHY USING ASCII
MAPPING TECHNOLOGY (AMT)
In this paper a new method of text steganography for English
language has been introduced. In the conventional text
steganography methods changes occurs between the cover and
stego text but in this AMT approach there is no reflection of
visual changes between cover and stego text occurs. In this
method cover text and secret message both are generated by
user. Stego text is formed by mapping the binary sequence of
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the secret message through the ASCII mapping technique of
some alphabets of the cover text. Figure 5 and 6 below
respectively shows the mapping sequence for embedding 0s
and 1s through the ASCII mapping technique of some of the
alphabets of the cover text. These ASCII mapping technique
have been incorporated using some unused symbols in the
ASCII chart. This method duplicates some of the alphabets
as shown in figure 4 and 5 to some unused ASCIIs of the
English language for embedding/mapping 0s and 1s
respectively. Before mapping operation derived quantum
logic has been used for selecting the valid embedding or
mapping positions which added an extra level of security.
Figure 4: Mapping sequence for embedding ‘0’
Figure 5: Mapping sequence for embedding ‘1’
3.1 Derivation of the Quantum Logic
Authors have derived quantum logic through the combination
of C-NOT gate, SWAP gate and quantum NOT gate. The
figure 6 below illustrates the steps of the derivation.
Figure 6: Derivation steps of the Quantum Logic
As shown in the figure 6 there is a OR operation has been
carried out between C-NOT gate and SWAP gate to generate
1st derived gate which in turn logically ORed with NOT gate
results the desired quantum logic, used to increase an extra
level of security.
3.2 Extra Level of Security through
Quantum Logic
As discussed in earlier section the quantum logic has been
incorporated to provide an extra level of security. The derived
quantum principle is placed over the cover text in a grid
format and the 1‟s generated signifies valid embedding
positions where 0‟s makes the embedding positions invalid.
Figure 7 shows a sample cover text where the underlined
letters are the embedding positions. After applying derived
quantum logic (as shown in figure 8) over that cover text
some embedding positions are discarded as marked in figure
9. The encrypted POS file contains the positional values of 0‟s
from the secret messages and the user can decrypt it and
compare with the secret message which has been extracted
from the stego text for authentication. This encryption of POS
file is done using integer wavelet transform (discussed in
section 4.2).
Figure 7: A Sample Cover Text
Figure 8: Derived quantum logic
Figure 9: After applying derived quantum logic, circular
letters are discarded as embedding positions.
4. MATHEMATICAL FORMULATION
OF THE PROCESSES
In this section the necessary essence of mathematical
formulation of the algorithms are discussed.
4.1 Quantum Gates
Quantum circuit model of computation in quantum computing
[30], [31] and [32], a quantum gate or quantum logic gate is a
basic quantum circuit which operates on a small number of
qubits or quantum bits. They are the building blocks of
quantum circuits, like classical logic gates are basically for
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conventional digital circuits. Quantum logic gates are
reversible like other classical logic gates. However, classical
computing can be performed by the help of only reversible
gates. Quantum gates are represented as matrices. A gate
which acts on k qubits is represented by a 2k x 2k unitary
matrix. The number of qubits in the input and output of the
gate is equal. There are various types of quantum gates are
represent the qubits. They are Hadamard gate, Pauli-X gate,
Pauli-Y gate, Pauli-Z gate, Phase shift gates, Swap gate,
Controlled gates, Toffoli gate, Fredkin gate, etc. Here we use
Controlled gates to represent the qubits and control the
operations. In this paper authors have used three quantum
gates i.e. NOT gate, CNOT gate, SWAP gate. The figure 10,
11, 12 shows the truth table of these gates.
Figure 10: NOT gate
Figure 11: C NOT gate
Figure 12: SWAP gate
It can also write this in the form of a matrix, or as a graphic.
The matrix form lists the lines in the truth table in the form
<0>, <1>. The matrix field with 1's and 0's such that each
horizontal or vertical line has exactly one 1, which is to be
interpreted as a one-to-one mapping of the input to the output.
The controlled gates act on 2 or more qubits, where one or
more qubits act as a control for some operation. For example,
the controlled not gate (or C-NOT) acts on 2 qubits, and
performs the NOT operation on the second qubit only when
the first qubit is , and otherwise leaves it unchanged. The
swap gate swaps two qubits.
4.2 Integer Wavelet Transform
Authors have used integer wavelet transform [33-35] as the
encryption function to encrypt the pos file which ensures that
the message is sent from an authorized end. The integer
wavelet transform through lifting scheme is an algorithm to
calculate wavelet transforms in an efficient way. It is also a
generic method to create so-called second-generation
wavelets. They are much more flexible and can be used to
define wavelet basis on an interval or on an irregular grid, or
even on a sphere. The wavelet lifting scheme is a method for
decomposing wavelet transform into a set of stages. An
advantage of lifting scheme is that they do not require
temporary storage in the calculation steps and have required
less no of computation steps. The lifting procedure consists of
three phases, namely, (i) split phase, (ii) predict phase and (iii)
update phase. Figure 13 shows the lifting scheme forward
wavelet transformation
Figure 13: Lifting Scheme Forward Wavelet
Transformation
Splitting: Split the signal x into even samples and odd
samples:
𝒙𝒆𝒗𝒆𝒏 : 𝒔𝒊 ← 𝒙𝟐𝒊 .
𝒙𝒐𝒅𝒅 : 𝒅𝒊 ← 𝒙𝟐𝒊+𝟏 .
Prediction Predict the odd samples using linear interpolation:
𝒅𝒊 ← 𝒅𝒊 − {(𝒔𝒊 + 𝒔𝒊+𝟏)/𝟐} .
Update: Update the even samples to preserve the mean value
of the samples:
𝒔𝒊 ← 𝒔𝒊 − {(𝒅𝒊−𝟏 + 𝒅𝒊)/𝟒} .
The output from the s channel provides a low pass filtered
version of the input where as the output from the d channel
provides the high pass filtered version of the input. The
inverse transformed is obtained by reversing the order and the
sign of the operations performed in the forward transform.
Figure 14 demonstrates the lifting scheme inverse wavelet
transformation.
Figure 14: Lifting Scheme Inverse Wavelet
Transformation
4.3 Lifting Scheme Haar Transform
In the lifting scheme version of the Haar transform, the
prediction step predicts that the odd element will be equal to
the even element. The difference between the predicted value
(the even element) and the actual value of the odd element
replaces the odd element. For the forward transform iteration j
and element i, the new odd element, j+1,i would be
𝒐𝒅𝒅𝒋+𝟏,𝒊 = 𝒐𝒅𝒅𝒋,𝒊 − 𝒆𝒗𝒆𝒏𝒋,𝒊
In the lifting scheme version of the Haar transform the update
step replaces an even element with the average of the
even/odd pair (e.g., the even element si and its odd successor,
si+1):
𝒆𝒗𝒆𝒏𝒋+𝟏,𝒊 =𝒆𝒗𝒆𝒏𝒋,𝒊 + 𝒐𝒅𝒅𝒋,𝒊
𝟐
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The original value of the oddj,i element has been
replaced by the difference between this element and its
even predecessor. Simple algebra lets us recover the
original value:
𝒐𝒅𝒅𝒋,𝒊 = 𝒆𝒗𝒆𝒏𝒋,𝒊 + 𝒐𝒅𝒅𝒋+𝟏,𝒊
Substituting this into the average,
𝒆𝒗𝒆𝒏𝒋+𝟏,𝒊 =𝒆𝒗𝒆𝒏𝒋,𝒊 + 𝒆𝒗𝒆𝒏𝒋,𝒊 + 𝒐𝒅𝒅𝒋+𝟏,𝒊
𝟐
𝒆𝒗𝒆𝒏𝒋+𝟏,𝒊 = 𝒆𝒗𝒆𝒏𝒋,𝒊 +𝒐𝒅𝒅𝒋+𝟏,𝒊
𝟐
5. SOLUTION METHODOLOGY
The proposed method contains of the following two windows.
One is for sender side and one is for receiver side. The sender
side takes the secret message and covers text, as an input and
generates secret key, stego text and an encrypted pos file as
output. The user should be able to generate secret message
and cover text. The receiver side takes stego text and the
encrypted pos file as input and retrieves the secret message.
The user should be someone who is familiar with the process
of information hiding and will have the knowledge of
steganography system. Figure 15 and 16 shows the proposed
methods for the corresponding GUI for the sender and
receiver side of the proposed text steganography system
respectively.
6. ALGORITHMS
In this section different algorithmic approach for embedding
and extraction process has been discussed. The secret message
is converted into bits by their ASCII values and the secret bits
are embedded through the embedding algorithm into the cover
text to generate the stego text.
6.1 Algorithm for Embedding
Let COVER is cover text and STEGO is the string which
consists of the stego text and MSG is the binary string of the
secret message and N is the no of elements in the MSG.
Initially COVER and STEGO are the same. Set two counters i
, p , j and r initialize to 1. POS is an array which contains the
positions of “0” bits of MSG and ENCRYPT is the function
which encrypts a value using INTEGER WAELET
TRANSFORM. QG contains the value of the derived
quantum logic.
Step 1: Generate an appropriate COVER consisting of “a” or
“m” or “n” and “i”, “j”, “k” Let l be the size of the
COVER. Copy the contents of the COVER into STEGO.
Step 2: For j=1to l
Step 3: If QG(i)==1 then do
goto step 4 and i:=i+1
Else
j:=j+1, i:=i+1
Step 4: If (COVER(j)== “a” or “m” or “n” and MSG(r)==
“1”)
then STEGO(j) := “a” or “m” or “n” and r :=
r+1
Else if (COVER(j)== “i” or “j” or “k” and MSG(r)==
“0”)
then STEGO(j) := “i” or “j” or “k” and r := r+1
Step 5: End of IF statement
Step 6: End of IF statement
Step 7: End of For loop
Step 8: For i=1 to N
Step 9: If (MSG(i)== “0”)
then pos(p)= ENCRYPT(i) and p := p+1
Step 10: End of If
Step 11: End of For loop
Step 12: End
6.2 Algorithm for Extraction
Let STEGO is the stego text and MSG is the binary string of
the secret message and N is the no. of elements in the STEGO
and i and r be two arbitrary variables and j is initialize to 1.
POS is an array which contains the positions of “0” bits of
MSG and DECRYPT is the function which reverses the
encrypt action on a value LENGHT (MSG) gives the length of
the secret message. SP is the number of element in the POS.
Step 1: For i=1 to N
Step 2: If ( STEGO(i)== “a” or “m” or “n”)
then MSG(r) := 1
Else if ( STEGO(i)== “i” or “j” or “k”)
then MSG(r) := 0
Step 3: End of If statement
Step 4 : End of For Loop
Step 5: For i=1 to SP
Step 6: IF(MSG(DECRYPT(POS(i))) == 0)
then message is authentic.
Step 7: End of If statement
Step 8: End of For loop
Step 9: End
7. ANALYSIS OF THE RESULT
There are mainly three aspects should be taken into account
when discussing the results of the proposed method of text
steganography. They are security, capacity and robustness.
The authors simulated the proposed system the results are
shown in the figure 17, 18, 19 and 20 respectively. This
method serves with better embedding capacity, security as
well as authentication aspect also. It generates the stego text
with zero degradation which is not very revealing to people
about the existence of any hidden data, maintaining its
security to the eavesdroppers. The embedding capacity
increases as the size of the cover text increases and the
encrypted file pos takes care of the authentication.
7.1 Similarity Measure of the Cover Text
and Stego Text through Shannon Entropy
Measure
Shannon entropy is one of the most important metrics in
information theory. Entropy measures the uncertainty
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associated with a random variable, i.e. the expected value of
the information in the message [36]. Shannon entropy allows
estimating the average minimum number of bits needed to
encode a string of symbols based on the alphabet size and
frequency of the symbols. The Shannon entropy is calculated
using formula:
𝑯 𝑿 = 𝒑 𝒙𝒊 𝑰 𝒙𝒊 =
𝒏
𝒊=𝟏
𝒑 𝒙𝒊 𝒍𝒐𝒈𝒃
𝟏
𝒑 𝒙𝒊
𝒏
𝒊=𝟏
= − 𝒑 𝒙𝒊 𝒍𝒐𝒈𝒃 𝒑 𝒙𝒊
𝒏
𝒊=𝟏
Shannon entropy tells about the minimal number of bits per
symbol needed to encode the information in binary form.
Additionally, other formulas can be calculated, one of the
simplest is metric entropy which is Shannon entropy divided
by string length. Metric entropy will helps to assess the
randomness of the message. It can take values from 0 to 1,
where 1 means equally distributed random string.
7.2 Similarity Measure of the Cover Text
and Stego Text through Correlation
The most familiar measure of dependence between two
quantities is the Pearson product-moment correlation
coefficient [37], or ”Pearson‟s correlation.” It is obtained by
dividing the covariance of the two variables by the product of
their standard deviations. Karl Pearson developed the
coefficient from a similar but slightly different idea by Francis
Galton. The Pearson correlation is +1 in the case of a perfect
positive (increasing) linear relationship (correlation), -1 in the
case of a perfect decreasing (negative) linear relationship (anti
correlation) , and some value between -1 and 1 in all other
cases, indicating the degree of linear dependence between the
variables.
As it approaches zero there is less of a relationship (closer to
uncorrelated). The closer the coefficient is to either -1 or 1,
the stronger the correlation between the variables. If the
variables are independent, Pearson‟s correlation coefficient is
0, but the converse is not true because the correlation
coefficient detects only linear dependencies between two
variables. If there is a series of n measurements of X and Y
written as xi and yi where i = 1,2,…,n then the sample
correlation coefficient can be used in Pearson correlation r
between X and Y. The sample correlation coefficient is
written as
𝑟𝑥𝑦 = 𝑥𝑖 − 𝑥 𝑛
𝑖=1 𝑦𝑖 − 𝑦
(𝑛 − 1) 𝑠𝑥 𝑠𝑦
where and are the sample means of X and Y, sx and sy
are the sample standard deviations of X and Y.
Figure 15: GUI for Sender Side
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Figure 16: GUI for Receiver Side
Figure 17: Cover text
Figure 18: Secret Message
Figure 19: Unicode Form of The Secret Message
Figure 20: Stego Text
7.3 Similarity Measure of the Cover Text
and Stego Text through Jaro Winkler
Distance
For comparing the similarity between cover text and the stego
text, the Jaro-Winkler distance for measuring similarity
between two strings has been computed. The Jaro-Winkler
distance [38] is a measure of similarity between two strings. It
is a variant of the Jaro distance metric [39], [40] and mainly
used in the area of record linkage (duplicate detection). The
higher the Jaro-Winkler distance for two strings is, the more
similar the strings are. The score is normalized such that 0
equates to no similarity and 1 is an exact match. The Jaro
distance metric states that given two strings s1 and s2 their
distance dj is
m
tm
s
m
s
md j
213
1 , where m is
the number of matching characters and t is the number of
transpositions. Two characters from s1 and s2 respectively are
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considered matching only if they are not farther than
12
,max 21
SS
. Each character of s1 is compared with
all its matching characters in s2. The number of matching (but
different sequence order) characters divided by two defines
the number of transpositions. Table 1 shows below the various
similarity coefficients of the different sizes of cover text
embedded with different secret message size.
Table 1: Similarity coefficient between different cover
text and stego text
8. COMPARISON WITH OTHER
METHODS
In this section a comparison has been shown with some other
existing methods like Text steganography using Changing
word spelling [27], Inter word spacing and inter paragraph
spacing [20] or Text Steganography by using Letter Points
and Extensions [28] or Text steganography using
CALP[24,25]. From the comparative study shown in table 2 it
has been observed that the proposed AMT Text
Steganography method is better than the existing other
methods in terms of embedding capacity and robustness. This
method supports the authentication of the secret message.
This method is a universal one and applicable to any other
languages. A technique for measuring the similarity between
the cover text and stego text also exist for this method.
9. CONCLUSION
In this paper a novel approach of English text steganography
method known as AMT has been presented .Stego text is
generated by mapping the binary sequence of the secret
message using ASCII mapping technique. Quantum logic
technique for finding valid embedding position increases an
additional level of security. This method takes care of the
authentication problem also through POS file. From Table 1 it
has been observed that AMT method generates the stego text
with minimum or zero degradation as the Shannon Entropy,
Correlation-coefficient and Jaro Score value is very high. This
property enables the method to avoid the steganalysis. The
proposed steganography technique through ASCII mapping is
a new approach for the English steganography and this
methodology can be extended to any other Indian language
also.
Table 2: Comparison of the proposed method with others
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