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Steganography by Multipoint Arabic Letters


Abstract and Figures

Security methodologies are taken into consideration for many applications, where transferring sensitive data over network must be protected from any intermediate attacker. Privacy of data can be granted using encryption, by changing transmitted data into cipher form. Apart from encryption, hiding data represents another technique to transfer data without being noticeable by an attacker. This technique is called Steganography. In this paper, we will discuss the main concepts of Steganography and a carrier media that is used for this goal. Employing text as mask for other text represents the most difficult method that can be used to hide data. We will discuss some algorithms that use Arabic text. We then describe our doted space methodology to enhance data hiding.
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Steganography by Multipoint Arabic Letters
Ammar Odeh, Aladdin Alzubi, Qassim Bani Hani, Khaled Elleithy
Department of Computer Science & Engineering,
University of Bridgeport
Bridgeport, CT 06604, USA
Abstract-Security methodologies are taken into consideration for
many applications, where transferring sensitive data over
network must be protected from any intermediate attacker.
Privacy of data can be granted using encryption, by changing
transmitted data into cipher form. Apart from encryption, hiding
data represents another technique to transfer data without being
noticeable by an attacker. This technique is called
Steganography. In this paper, we will discuss the main concepts
of Steganography and a carrier media that is used for this goal.
Employing text as mask for other text represents the most
difficult method that can be used to hide data. We will discuss
some algorithms that use Arabic text. We then describe our doted
space methodology to enhance data hiding.
Keywords: Steganography, carrier file, text steganograph, image
steganography, audio steganography, information hiding,
Persian/Arabic Text, steganalysis, stego medium, stego_key.
A. Background
Steganography is a Greek word coming from cover text.
"Stegano" means hidden and “Graptos" means writing. In
steganography, the secure data will be embedded into another
object, so middle attacker can't catch it [1]. Invisible ink is an
example for Steganography using a readable message transfer
between source and destination. Everyone in the middle can
read the message without having any clue about the hidden
data. On other hand, authorized persons can read it depending
on the substances features [2][3].
Ancient Greeks used to shave the messenger head and then
wait until the hair grew back. That is when the message will be
sent to the destination [1]. Depending on this method, there are
two possibilities:
1. Message has arrived so the receiver can read the message
and recognize if message has changed or not.
2. If message did not arrive, it means the attacker has
detected the message.
B. Motivation
Steganography algorithms depend on three techniques to
embed the hidden data in the carrier files.
1. Substitution: Exchange a small part of the carrier file by
the hidden message where the middle attacker cannot observe
the changes on the carrier file. On the other hand, in choosing
a replacement process, it is very important to avoid any
suspicion. This means that it is important to select
insignificant parts from the carrier file and then replace them.
For instance, if the carrier file is an image (RGB), then the
least significant bit (LSB) can be used as the exchange bit [4].
2. Injection: By adding hidden data into the carrier file, the
file size will increase and this will increase the suspicion. So
the main goal to present techniques to add hidden data while
avoiding attacker suspicion [4].
3. Propagation: There is no need for a cover object. It
depends on using a generation engine fed by input (hidden
data) to produce and mimic a file (graphic or music or text
document ).
The Steganography process consists of three main
components as show in Figure 1.
Figure 1. General components of Steganography
Different types of cover media including image, sound,
video and text can be used in Steganograph, as shown in
Figure 2. Choosing carrier file is very sensitive where it plays
a key role to protect the embedded message. Successful
Steganography depends on avoiding suspicion. Steganalysis
will start checking the file. If there is any suspicion, this will
compromise the main goal of Steganography [3][4].
Figure 2. Stego Media
Text Steganography represents the most difficult type,
where there is generally lack of data redundancy in the text file
in comparison with other carrier files [5]. The existence of
such redundancy can help increase the capacity of hidden data
size. Furthermore, text Steganography depends on the
language, as each language has its own unique characteristics
which is completely different from other languages. For
example, the letter shape in English language does not depend
on its position in the word, while Persian/Arabic letters have
different forms depending on letter positioning [6].
In our new proposed algorithm, we hide text inside text by
employing Arabic language and applying a random algorithm
to distribute the hidden bits inside the message. The main
reasons for choosing the Arabic language are:
1. The proposed algorithm will depends on multi dotted
points letters. Therefore, the algorithm must employ a
language that has as many as possible dotted letters. For
example, the Arabic Language has 5 multipoint letters and
Persian/Farsi language has 8 letters [7], while English does not
have any.
2. Wealth availability of electronic textual information.
3. There is little research on other languages compared to
4. The approach can be extended to other languages like Urdu
and Kurdish.
C. Main Contribution and Paper Organization
An efficient algorithm is presented in this paper. The main
idea is to use multiple point characters in Arabic which
enables us to hide more than two bits per letter. The rationale
behind this approach is that most of the previous algorithms
reported in literature hide one bit for one letter. Furthermore,
we will merge our algorithm with vertical shifting point
algorithm to increase the size of the hidden file. The size of the
carrier will be constant without any change. After we add the
data, we convert the file into image to avoid the retyping
The rest of this paper is organized as follows. In section II,
we discuss some text Steganography techniques as well as
their advantages and disadvantages. Our multipoint hidden
algorithm is discussed in section III. In section IV, we present
experimental results of our algorithm. Finally, conclusions are
presented in section V.
Text Steganography is divided into two categories. The
first one is the semantic method, and the second is the
formatting method, as shown in Figure 2. In this Section we
will briefly explain some Steganography examples. In Table I,
we present a simple comparison between semantic and
formatting methods.
Table I. Comparison between text Steganography methods
Semantic Method Format Method
Amount of hidden
Small amount More than semantic
Flaws Sentence meaning notice from OCR or
Steganography criteria will depend on the amount of data
that can be hidden and the main problem facing the method.
We describe ten algorithms that hide data inside text
documents. The last two algorithms deal with Arabic and
Persian languages.
1. Word Synonym
Word Synonym is also called semantic method and it
depends on replacing some words by their synonym. See
Table II. This technique will convey data without making any
suspicion. It is limited in terms of that fact that hidden data
will be small relative to other methods. Moreover, it may
change the sentence meaning [7][10][12].
2. Punctuation
This method uses punctuation like (.)(;) to represent hidden
text. For example "NY, CT, and NJ" is similar to "NY, CT and
NJ" where the comma before the “and” represents 1, and the
other represents 0. The amount of hidden data in this method
is very small compared to the amount of cover media.
Inconsistence use of punctuation will be noticeable from
Steganoanalysis point of view [9].
Table II. Using Word Synonym
Word Synonym
Big Large
Find Observe
Familiar Popular
Dissertation Thesis
Chilly Cool
3. Line Shifting
Line shifting means to vertically shift the line a little bit to
hide information to create a unique shape of the text.
Unfortunately, line shifting can be detected by a character
recognition program. Moreover retyping removes all hidden
data [7][10].
In Figure 3, we present an example regarding line shifting
where the vertical shifting is very small (1/300 inch). This is
not noticeable by the human eye.
Figure 3. Line shifting; second line is shifted up 1/300 inch
4. Word Shifting
In this method, changing spaces between words enables us
to hide information. Word shifting is noticeable by OCR
through detecting space sequence between words [7][10].
5. SMS Abbreviations
Recently most SMS messages use abbreviations for
simplicity and security while used in different applications
such as internet chatting, email, and mobile messaging. The
main advantage of this method is to speed typing, reducing the
message’s length and manipulated keyboard limitation
character [13].
Other algorithms use numbers to convey specific
information. As mentioned above, SMS abbreviation can be
used in specific applications while using in others creates
suspicion of any entity that monitors the ongoing transmission.
Table III. Some SMS Abbreviations
Abbreviation Meaning
ADR Address
ABT About
URW You are welcome
ILY I love you
EOL End of lecture
AYS Are you serious?
6. Text Abbreviations
Text abbreviation is similar to SMS abbreviation, where a
dictionary is created for each word abbreviation and its
meaning. The dictionary is published between the
communication parties. Abbreviation represents one method to
hide data. For example if you send (see) it means (do you
understand) [13].
7. HTML Spam Text
This method depends on HTML pages, where their tags
and their members are insensitive. For example <BR> equal to
<Br>, and the same as <br> and <bR>. The hidden data
depends on upper case or lower case letters to embedd 0 or 1.
8. TeX Ligatures
In TeX ligatures, some special groups of letters can be
joined together to create a single glyph as shown in Figure 4.
The algorithm finds available ligatures in the text to hide a
single bit in each one. For example, if we want to hide 1 we
write fi to f {}i which creates some space between f and i.
Otherwise, we encode 0 [5].
The same algorithm can be applied to Arabic character ""
or " ل". This algorithm has two problems. The first problem is
that file size increases when we apply extension in our text.
The second problem is that if the ORC notices the font change,
it can detect the decoding hidden message [6][5].
9. Arabic Diacritics
Arabic language uses different marks. The main reason to
use these symbols is to distinguish between words that have
same letters. It depends on Arabic Diacritics (Harakat), where
diacritics are optional. Most of Arabic novels can be read
without Diacritics which depends on the language’s grammar.
The most occurrence is Fatha " َ " which will be used to
encode 1 otherwise encode 0.Our new algorithm will enhance
the reuse of cover media. Furthermore, the carrier file size
might be reduced depending on the hidden message. On the
other hand, when ORC detects the same message with
different diacritics, it might conclude that there is a hidden
data. In addition, retyping will remove the embedded message
Figure 4 .Join between characters [5]
Table IV. Some Letters with mark and their Pronunciation
Pronunciation Letter with
Do ُد Dama
De ِد Kasra
Da َد Fatha
10. Vertical Displacement of the Points
This algorithm achieves excellent performance as it is
applied on pointed (dotted) letters. Other languages such as
English language have only two dotted letters; {i, j}; and thus
limits the application of this algorithm. Alternatively, some
languages such as Arabic and Persian have many pointed
letters which make them fit better for this technique.
Arabic and Persian languages have many pointed
characters. Arabic has 26 letters where 13 of them are pointed,
and Persian has 32 letters where 22 of them are pointed. In this
new algorithm, we encode 1 to shift up the point, otherwise
encode 0. This method can encode a huge number of bits, and
need a strong OCR to recognize the changes. Meanwhile,
retyping will remove the entire message [7].
Figure5. Vertical shifting point [7]
Pointed letters represents one of the important
characteristics of Arabic and Persian languages. Table II
classifies Arabic letter with respect to the number of points.
Table V Arabic letters with respect to the number of points
Letter Number of points
ا,ح,د,ر,ص,ط,ع,ك,ل,,و 0
ب,ج,خ,ذ,ز,ض,ظ,غ,ف,ن 1
ت,ق,ي 2
ث,ش 3
Our algorithm hides data in multipoint Arabic/Persian
letters like (ث, tha). In Arabic language, there are five multi-
pointed letters, and in Persian there are eight. Each character
can be used to hide 2 bits to determine the shifting and
distance between letter points. Table III represents the relation
between letter, shifting, and encoding
Table VI represents relation of shifting and distance to
letter format
distance code Letter effects
0 0 00 No change
0 1 01 Only distance between
point increase
1 0 10 Only little upper
1 1 11 Upper shifting and
increase distance
between point
A. Pseudo Code and Flow Chart
In this subsection we present the pseudo-code and
flowchart of the proposed Arabic multipoint steganography
algorithm. The flowchart of the algorithm is shown in Figure
7. The pseudo-code follows:
1. Enter the text and hidden file and its size
2. Search for multipoint letters
3. Hide size of embedded data at the beginning
4. For I= start to EOF
IF hidden data ="00" then call Nochange();
Else if hidden data= "01" then call distance ();
Else if hiddendata ="10" then call shifting ();
Else if hiddendata="11" then call
Else random call for any one // for padding purpose
End for
5. Convert file to image file and send to other side
6. End
As can be seen in the above pseudo-code, in step 5, the file
must be converting to image file for transfer. The receiver will
scan the image file and find out the multipoint letters and then
classify the function applied on it.
B. Advantages and Disadvantages
Our multipoint algorithm has many advantages, as one
character can hide 2 bits compared to other algorithms that can
hide 1 bit per letter. This implies that the amount of hidden
data can be duplicated. Furthermore, the number of changed
characters for a given message, which leads to decrease which
leads to less suspicion. Moreover, the file size will have fewer
changes, since the number of changes in characters format is
On the other hand, any retyping process removes all the
hidden data, as the hidden data depends on the file format. The
consistent format used in the system might raise the level of
suspicion of an attacker.
A. Multipoint algorithm
Our algorithm depends on multipoint letters to include
hidden data. For this reason, we test different websites that
contain text and picture.
We will run two files in parallel for carrier file and hidden
data file. This process we will use two bits for each letter by
applying the distance_shifting algorithm.
Figure 6. Parallel operation carrier file and hidden data
As shown in Figure 6, after we merge the hidden data, we
convert it to image file to prevent the issues caused by
retyping. After that, we can compress the file to produce the
compressed image. The receiver decompresses the image and
then extracts the hidden data.
B. Experimental Results of the Multipoint Algorithm
Table VII Capacity of webpage for different Arabic website
# Page Name
# 2 point
or more
HD: Hidden Data
EOF: End of File
Figure 7. Flowchart of multipoint algorithm
As shown in Table VII, we used different Arabic news
websites to observe the data ratio that can be hidden in each
C. Analysis of the Algorithm
Our algorithm is compared to the vertical shifting
algorithm in terms of the number of changing letters and the
number of bits that can be hidden. In Table VIII, the result of
testing one paragraph is shown. The total number of letters is
115 which indicates that 42% of it is pointed. On the other
hand, the number of multipoint letters is 29, which indicates
25%. The data that can be hidden in the multiple point
algorithm is more than the first one. So we calculate the
efficiency depending on Equation 1:
E= #of hidden characters / #of characters *100% (1)
where E is the efficiency.
So, the efficiency of multiple points is 50% while vertical
point shifting is 43%.
Table VIII Vertical Point shifting versus Multipoint
فﺮﻌﺘﻟا ﻦﻜﻤ ﻪﻧأ ﻦﻴﻴﻧﺎﻄﻳﺮﺒﻟا ﻦﻴﺜﺣﺎﺒﻟا ﻦﻣ ﺔﻋﻮﻤﺠﻣ ﺎهاﺮﺟأ ﺔﺜﻳﺪﺣ ﺔﺳارد ﺘﺒﺛأ
ﻪﺗرﺎﻴﺳ عﻮﻧ ﻲﻓ ﻖﻴﻗﺪﺘﻟا لﻼﺧ ﻦﻣ صﺎﺨﺷﻷا ﺾﻌﺑ ﺔﻴﺼﺨﺷ ﺢﻴﺗﺎﻔﻣ ﻰﻠﻋ
Number of letter Number of
hidden bit
Pointed letter 50 50
Multipoint letter 29 58
D. Merge with Vertical Point Shifting
In this subsection, we calculate the ratio when we
compound the vertical point shifting algorithm discussed in [7]
with the multipoint algorithm.
Figure 8. Merging vertical and multipoint algorithms
In Figure 8, we note the ability of the vertical point
algorithm to hide huge amount of data as compared to the
multipoint algorithm. On the other hand, an observer can
notice the vertical changes more than multipoint changes
where the number of changes will be more. Consequently, the
merging both algorithms gives us better idea and flexibility in
hiding data and those that can be detected by an observer.
In this paper we introduce a new text Steganograph for
Arabic multipoint letters. The new algorithm deals with two
bits for each multipoint letter. We combine our strategy with
vertical point shifting [7] to improve the amount of hidden
The retyping process is a challenging problem for similar
algorithms which removes all the hidden data. We solve this
challenge to mitigate any new font format changes by unifying
all data which leads a homogenous file. Finally, the result
reported by this implementation has outperformed similar
results reported in literature in terms of the hiding capacity and
the possibility of having such steganography mechanism used
in hiding information.
[1] Aelphaeis Mangarae "Steganography FAQ," Zone-H.Org March
18th 2006.
[2] S. Dickman, "An Overview of Steganography," July 2007.
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Steganographic Carrier," Proceedings of the 4th International
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Ammar Odeh is a PhD. Student in University of
Bridgeport. He earned the M.S. degree in Computer
Science College of King Abdullah II School for
Information Technology (KASIT) at the University
of Jordan in Dec. 2005 and the B.Sc. in Computer
Science from the Hashemite University. He has
worked as a Lab Supervisor in Philadelphia
University (Jordan) and Lecturer in Philadelphia
University for the ICDL courses and as technical
support for online examinations for two years. He
served as a Lecturer at the IT, (ACS,CIS ,CS)
Department of Philadelphia University in Jordan,
and also worked at the Ministry of Higher
Education (Oman, Sur College of Applied Science)
for two years. Ammar joined the University of
Bridgeport as a PhD student of Computer Science
and Engineering in August 2011. His area of
concentration is reverse software engineering,
computer security, and wireless networks.
Specifically, he is working on the enhancement of
computer security for data transmission over
wireless networks. He is also actively involved in
academic community, outreach activities and
student recruiting and advising.
Qassim Bani Hani is Ph.D. candidate of computer
science and Engineering department in the
University of Bridgeport. His current research
interests include the design and development of
learning environment to support the learning about
heterogamous domain, collaborative discovery
learning and the development of mobile
applications to support mobile collaborative
learning (MCL), The congestion mechanism of
transmission of control protocol including various
existing variants, delivery of multimedia
applications. He completed his Bachelor degree in
computer science from Irbid National University in
2004 and Master degree in computer science from
Al-Balqa' Applied University in 2007. Qassim has
been directly involved in design and development of
mobile applications to support learning
environments to meet pedagogical needs of schools,
colleges, universities and various organizations.
Aladdin Alzubi received the B.Sc. in Software
Engineering from Philadelphia University, Amman,
Jordan in 2004, and the Master of Computer
Sciences from University Sians Malaysia –
Malaysia in 2006. In 2011 he joined University of
Bridgeport as Ph.D. student in computer science and
engineering at the University of Bridgeport,
Connecticut-USA. From 2000 to 2004.
Dr. Elleithy is the Associate Dean for Graduate
Studies in the School of Engineering at the
University of Bridgeport. He has research interests
are in the areas of network security, mobile
communications, and formal approaches for design
and verification. He has published more than one
hundred fifty research papers in international
journals and conferences in his areas of expertise.
Dr. Elleithy is the co-chair of the International Joint
Conferences on Computer, Information, and
Systems Sciences, and Engineering (CISSE). CISSE
is the first Engineering/Computing and Systems
Research E-Conference in the world to be
completely conducted online in real-time via the
internet and was successfully running for four years.
Dr. Elleithy is the editor or co-editor of 10 books
published by Springer for advances on Innovations
and Advanced Techniques in Systems, Computing
Sciences and Software.
... Firstly, high performance implementation; in English based nique using ECR technique has fast process embedding (Kataria et al., 2013), High invisibility in technique using Reversed Fatah technique (Memon et al., 2008) has standard model transition in Hindi (Changder et al., 2009) and in letter based using Back end interface web page (Mahato et al., 2013). Secondly, feature-based also can embed hidden text in large capacity likes in English based using Deoxyribonucleic Acid (DNA)technique (Reddy et al., 2014) and in Arabic based with reversed Fattah (Memon et al., 2008), vertical displacement technique (Odeh et al., 2012). In Hindi based technique of specific matra (Changder et al., 2010)) and chain code technique. ...
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... There is a contribution to protect contents by watermarks using Arabian letters where it has multipoint. From this advantage, it can be embedded 2 Byte instead of one Byte and there is no increase in the payload of the signal and it still maintains its imperceptibility [1]. The Digital Right Management (DRM) is one of aspect that studies how to control the cloud and the contents contained in. ...
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There are many contents have to be saved from stealing or abused by unauthorized users or groups in media's organization. In this work, watermarking is used for this purpose. A watermarking image that belongs to the organization is inserted into the content needed to be protected to help the owners for detecting any illegal use of it. Transforms like Discrete Cosine Transform (DCT), Discrete Sine Transform (DST) or Discrete Wavelet Transform (DWT) based on Fraction Fourier Transform (FracFT) are used to test which is suitable for the cloud and new tests are proposed to evaluate the performance of watermarking process in both case of embedding and extracting. The embedded factor is also evaluated to determine the best value for Egyptian Radio and Television Union (ERTU)'s cloud and then yield a good agreement which is done in this work. Many attacks are also defined to justify the algorithm's robustness and which can be used to obtain high quality services for the Authorized Groups (AuthGs). The ability to provide these services to AuthGs does not depend on the distance and the connection to the cloud.
Conference Paper
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This paper investigates eight novel Steganography algorithms employing text file as a carrier file. The proposed model hides secret data in the text file by manipulating the font format or inserting special symbols in the text file. Furthermore, the suggested algorithms can be applied to both Unicode and ASCII code languages, regardless of the text file format. In addition, a merging capability among the techniques is introduced, which allows alternatives for users based on the system requirements. The proposed algorithms achieve a high degree of optimized Steganography attributes such as hidden ratio, robustness, and transparency.
Conference Paper
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Different strategies were introduced in the literature to protect data. Some techniques change the data form while other techniques hide the data inside another file. Steganography techniques conceal information inside different digital media like image, audio, and text files. Most of the introduced techniques use software implementation to embed secret data inside the carrier file. Most software implementations are not sufficiently fast for real-time applications. In this paper, we present a new real-time Steganography technique to hide data inside a text file using a hardware engine with 11.27 Gbps hidden data rate. The fast Steganography implementation is presented in this paper.
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Different security strategies have been developed to protect the transfer of information between users. This has become especially important after the tremendous growth of internet use. Encryption techniques convert readable data into a ciphered form. Other techniques hide the message in another file, and some powerful techniques combine hiding and encryption concepts. In this paper, a new security algorithm is presented by using Steganography over HTML pages. Hiding the information inside Html page code comments and employing encryption, can enhance the possibility to discover the hidden data. The proposed algorithm applies some statistical concepts to create a frequency array to determine the occurrence frequency of each character. The encryption step depends on two simple logical operations to change the data form to increase the complexity of the hiding process. The last step is to embed the encrypted data as comments inside the HTML page. This new algorithm comes with many advantages, such as generality, applicability to different spoken languages, and can be extended to other Web programming pages such as XML, ASP.
Conference Paper
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The need for secure communications has significantly increased with the explosive growth of the internet and mobile communications. The usage of text documents has doubled several times over the past years especially with mobile devices. In this paper, we propose a new steganography algorithm for Unicode language (Arabic). The algorithm employs some Arabic language characteristics which represent extension letters. Kashida letter is an optional property for any Arabic text and usually is not popularly used. Many algorithms tried to employ this property to hide data in Arabic text. In our method, we use this property to hide data and reduce the probability of suspicions. The proposed algorithm first introduces four scenarios to add Kashida letters. Then, random concepts are employed for selecting one of the four scenarios for each round. Message segmentation principles are also applied, enabling the sender to select more than one strategy for each block of message. At the other end, the recipient can recognize which algorithm was applied and can then decrypt then message content and aggregate it. Kashida variation algorithm can be extended to other similar Unicode languages to improve robustness and capacity.
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In this paper, we are going to introduce different types of steganography considering the cover data. As the first step, we will talk about text steganography and investigate its details. Then, image steganography and its techniques will be investigated. Some techniques including Least Significant Bits, Masking and filtering and Transformations will be subjected during image steganography. Finally, audio steganography which contains LSB Coding, Phase Coding, Spread Spectrum and Echo Hiding techniques will be described.
Conference Paper
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Conveying information secretly and establishing hidden relationship has been of interest since long past. Text documents have been widely used since very long time ago. Therefore, we have witnessed different method of hiding information in texts (text steganography) since past to the present. In this paper we introduce a new approach for steganography in Persian and Arabic texts. Considering the existence of too many points in Persian and Arabic phrases, in this approach, by vertical displacement of the points, we hide information in the texts. This approach can be categorized under feature coding methods. This method can be used for Persian/Arabic Watermarking. Our method has been implemented by JAVA programming language.
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The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message. If suspicion is raised then this goal is defeated. The success of steganography, to a certain extent, depends on the secrecy of the cover medium. Once the steganographic carrier is disclosed then the security depends on the robustness of the algorithm used. Hence, to maintain secrecy either we have to make the cover medium more robust against steganalysis or discover new and better cover mediums. We consider the latter approach much more effective, since old techniques get prone to steganalysis. In this paper, we present one such cover medium. We propose to use ciphertext as a steganographic carrier. (114 words)
Conference Paper
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New steganography methods are being proposed to embed secret information into text cover media in order to search for new possibilities employing languages other than English. This paper utilizes the advantages of diacritics in Arabic to implement text steganography. Diacritics - or Harakat - in Arabic are used to represent vowel sounds and can be found in many formal and religious documents. The proposed approach uses eight different diacritical symbols in Arabic to hide binary bits in the original cover media. The embedded data are then extracted by reading the diacritics from the document and translating them back to binary.
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Data hiding, a form of steganography, embeds data into digital media for the purpose of identification, annotation, and copyright. Several constraints affect this process: the quantity of data to be hidden, the need for invariance of these data under conditions where a "host" signal is subject to distortions, e.g., lossy compression, and the degree to which the data must be immune to interception, modification, or removal by a third party. We explore both traditional and novel techniques for addressing the data-hiding process and evaluate these techniques in light of three applications: copyright protection, tamper-proofing, and augmentation data embedding.
Conference Paper
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Modern computer networks make it possible to distribute documents quickly and economically by electronic means rather than by conventional paper means. However, the widespread adoption of electronic distribution of copyrighted material is currently impeded by the ease of illicit copying and dissemination. The authors propose techniques that discourage illicit distribution by embedding each document with a unique codeword. The encoding techniques are indiscernible by readers, yet enable one to identify the sanctioned recipient of a document by examination of a recovered document. The authors propose three coding methods, describe one in detail, and present experimental results showing that their identification techniques are highly reliable, even after documents have been photocopied
Steganography is a useful tool that allows covert transmission of information over an overt communications channel. Combining covert channel exploitation with the encryption methods of substitution ciphers and/or one time pad cryptography, steganography enables the user to transmit information masked inside of a file in plain view. The hidden data is both difficult to detect and when combined with known encryption algorithms, equally difficult to decipher. This paper provides a general overview of the following subject areas: historical cases and examples using steganography, how steganography works, what steganography software is commercially available and what data types are supported, what methods and automated tools are available to aide computer forensic investigators and information security professionals in detecting the use of steganography, after detection has occurred, can the embedded message be reliably extracted, can the embedded data be separated from the carrier revealing the original file, and finally, what are some methods to defeat the use of steganography even if it cannot be reliably detected.
Conference Paper
By expanding communication, in some cases there is a need for hidden communication. Steganography is one of the methods used for hidden exchange of information. Steganography is a method to hide the information under a cover media such as image or text. One of the text steganography methods for Persian and Arabic texts is "La" steganography method. But that method increases the file size and changes the apparent of the text. In this paper a method for solving these problems is proposed. In Persian and Arabic, each letter can have four different shapes regarding to its position in the word. In this method by using this feature of Persian and Arabic languages and the way which documents are saved in the Unicode Standard, the above problems are solved.
Conference Paper
Steganography is a method for hidden exchange of information by hiding data in a cover media such as image or sound. Text Steganography is one of the most difficult methods because a text file is not a proper media to hide data in it. In this paper we propose a new text Steganography method. In this method, we hide data in TeX documents. This method hides the data in places where there is a ligature such as ¿fi¿.
Linguistic Steganography: Survey, Analysis, and Robustness Concerns for Hiding Information in Text " Center for Education and Research in Information Assurance and Security
  • K Bennett
K. Bennett, " Linguistic Steganography: Survey, Analysis, and Robustness Concerns for Hiding Information in Text " Center for Education and Research in Information Assurance and Security, Purdue University, 2004.