1
Data Security using Steganography
(Audio Steganography)
Enrollment. No. - 9911103519
Name of Student - Rajan Yadav
Name of supervisor(s) - Mr. Himanshu Agrawal
June - 2015
Submitted in partial fulfillment of the Degree of
Bachelor of Technology
In
Computer Science Engineering
DEPARTMENT OF COMPUTER SCIENCE ENGINEERING &
INFORMATION TECHNOLOGY
JAYPEE INSTITUTE OF INFORMATION TECHNOLOGY, NOIDA
2
(I)
TABLE OF CONTENTS
Chapter No. Topics Page No.
Student Declaration 4
Certificate from the Supervisor 5
Acknowledgement 6
Summary 7
List of Figures 8
List of Tables 9
List of Symbols and Acronyms 10
Chapter-1 Introduction 11-13
1.1 General Introduction
1.2 General problem with Steganography
1.3 Problem Statement
1.4 Benefits of proposed Solution
Chapter-2 Background Study 14-20
2.1 Literature Survey
2.1.1 Summary of papers
2.1.2 Integrated summary of the literature studied
Chapter 3: Analysis, Design and Modeling 21-28
3.1 Requirements Specifications
3.2 Functional and Non Functional requirements
3.3 Design Documentation
3.3.1 Use Case diagrams
3.3.2 Control Flow Diagrams
3.3.3 Activity diagrams
3.4 Risk Analysis and Mitigation Plan
3
Chapter-4 Implementation and Testing 29-34
4.1 Implementation details and issues
4.2 Testing
4.2.1 Testing Plan
4.2.2 Component decomposition and type of testing required
4.2.3 List all test cases in prescribed format
4.2.4 Limitations of the solution
Chapter-5 Findings & Conclusion 35
5.1 Findings
5.2 Conclusion
5.3 Future Work
Appendices
Gantt Chart 36
References 37
Bio-data (Resume) of Student 38-39
4
(II)
DECLARATION
I hereby declare that this submission is my own work and that, to the best of my
knowledge and belief, it contains no material previously published or written by another
person nor material which has been accepted for the award of any other degree or diploma
of the university or other institute of higher learning, except where due acknowledgment
has been made in the text.
Place: ……………………. Signature:
Date: ……………………. Name: Rajan Yadav
Enrollment No: 9911103519
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(III)
CERTIFICATE
This is to certify that the work titled “Data Security using Steganography” submitted
by “Rajan Yadav” in partial fulfillment for the award of degree of B.Tech of Jaypee
Institute of Information Technology University, Noida has been carried out under my
supervision. This work has not been submitted partially or wholly to any other University
or Institute for the award of this or any other degree or diploma.
Signature of Supervisor …………………….
Name of Supervisor: Mr. Himanshu Agrawal
Designation: Assistant Professor, Department CSE/IT, JIIT, Noida
Date: …………………….
6
(IV)
ACKNOWLEDGEMENT
This project is done for the fulfilment of the Degree of Bachelor of Technology in
Computer Science and Engineering, as a part of Major Project II. I would like to thank
Mr. Himanshu Agrawal, my Project Mentor and Assistant Professor (Dept. of CSE/IT)
for guiding me in this project. His valuable advice, suggestions and motivation to help me
work in my area of interest have always been very encouraging.
I am also thankful to Dr. Charu (Assistant Professor) and Ms. Anuradha Gupta (Assistant
Professor), External Evaluators for Major Project who believed in my capabilities and
giving me the right direction by letting me know my drawbacks and gave the opportunity
to rectify my mistakes.
I owe my gratitude to Dr. Shelly Sachdeva (Major Coordinator-Assistant Professor) for
giving this opportunity to explore into the real world and realize the interrelation of
theoretical Concepts and its practical application of my own interest.
Signature of the Student ………………………
Name of Student Rajan Yadav
Enrollment Number 9911103519
Date ………………………
7
(V)
SUMMARY
Steganography is the art and science of writing hidden messages in such a way that no
one, apart from the sender and intended recipient, suspects the existence of the message,
a form of security through obscurity. Steganography works by replacing bits of useless or
unused data in regular computer files (such as graphics, sound, text, HTML, or even
floppy disks ) with bits of different, invisible information. This hidden information can
be plain text, cipher text, or even images.
In a computer-based audio Steganography system, secret messages are embedded in
digital sound. The secret message is embedded by slightly altering the binary sequence of
a sound file. Existing audio Steganography software can embed messages in WAV, AU,
and even MP3 sound files. Embedding secret messages in digital sound is usually a more
difficult process than embedding messages in other media, such as digital images. These
methods range from rather simple algorithms that insert information in the form of signal
noise to more powerful methods that exploit sophisticated signal processing techniques
to hide information.
Thereby I have chosen C# based windows application to serve the purpose. C# is world’s
most widely used window user based application platform. I have decided to make
application to serve the application of Audio Steganography.
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(VI)
LIST OF FIGURES
S. No Figure Details Page No
Figure 1 LSB encoding 18
Figure 2 Phase coding 19
Figure 3 Class Diagrams 23
Figure 4 DFD 0 Level 24
Figure 5 Activity Diagram(Embed) 25
Figure 6 Activity Diagram(Extract) 26
Figure 7 Risk Relation 38
Figure 8 Steganography module 30
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(VII)
LIST OF TABLES
S. No Table Description Page
number
Table 1 Risk Analysis 30
Table 2 Mitigation Plan 30
Table 3 Testing Plan 35
Table 4 Component Decomposition 35
Table 5 List of all test cases 36
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(VIII)
LIST OF SYMBOLS & ACRONYMS
Abbreviation Full Form
WAV Window Audio Video
IJACSA International Journal of Advance Computer
Science Application
IEEE Institute of Electrical and Electronic
Engineers
IJARCSM International Journal of Advance Research
in Computer Science and Management
Studies
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1. INTRODUCTION
1.1 General Introduction
Steganography derived from Greek steganos, or "covered," and graphie, or "writing") is
the hiding of a secret message within an ordinary message and the extraction of it at its
destination. Steganography takes cryptography a step farther by hiding an encrypted
message so that no one suspects it exists. Ideally, anyone scanning your data will fail to
know it contains encrypted data.
In modern digital steganography, data is first encrypted by the usual means and then
inserted, using a special algorithm into redundant (that is, provided but unneeded) data
that is part of a particular file format such as a JPEG image, text file, music file. Think
of all the bits that represent the different data repeated in a row. By applying the
encrypted data to this redundant data in some random or non-conspicuous way, the result
will be data that appears to have the "noise" patterns of regular, non-encrypted data. A
trademark or other identifying symbol hidden in software code is sometimes known as
a watermark .Steganography is mainly oriented around the undetectable transmission of
one of information within another. In order for a data hiding technique to be successful
it must adhere to two rules:
The embedded data must be undetectable within its carrier medium (the audio or
image file used). The carrier should display no properties that flag it as suspicious,
whether it is to the human visual/auditory system or in increased file size for the
carrier file.
The embedded data must maintain its integrity within the carrier and should be easily
removable, under the right circumstances, by the receiving party.
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1.2 General problem with Steganography
The biggest problem steganography faces is that of size. There is limit to the size of
message which you can embed into. For instance if we take a message of n length then
the no of samples in the audio has to be greater than the length in order to encode the bits
in audio file. As a result audio steganography is able to embed a large length file as a
particular wav file has large no of samples.
1.3 Problem Definition:
We are of the belief that the easiest way to keep something from interfering eyes is to
place it right in front of the person looking for it and make it look as innocuous as possible.
The primary goal of this project is to provide end users the ability to apply
steganography on wave audio files and secretly convey messages to the other end users.
This project mainly concentrates on applying steganography to audio files. As discussed
earlier, steganography can also be applied to video, image and text files. The main
emphasis of this project is on developing a tool for use in audio steganography. The
main purpose of tool is to transfer encrypted messages between two different parties.
Also emphasis is based on preventing the intruders from detecting the encrypted or
secret message.
Software is developed in such a way that it takes a wave file and the message to be
encrypted as inputs and create a new stego wave file. The encrypt method that will be
used encrypts the file to be hidden first and later embeds into the wave file.
The existing system of Audio Steganography poses more restrictions on the choosing of
audio files. User can select only wav files to encode. Further embedding information into
sound files is generally considered more difficult than images; according to the human
ear is extremely sensitive to perturbations in sound and can in fact detect such turbulence
as low as one part in 10 million. The four methods discussed further provide users with a
large amount of choice and makes the technology more accessible to everyone.
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1.4 Overview and Benefits of Proposed solution
Audio based Steganography has the potential to conceal more information:
Audio files are generally larger than images.
Our hearing can be easily fooled.
Slight changes in amplitude can store vast amounts of information.
The flexibility of audio Steganography makes it very potentially powerful.
The method discussed provide users with a large amount of choice and makes the
technology more accessible to everyone. A party that wishes to communicate can rank
the importance of factors such as data transmission rate, bandwidth, robustness, and
noise audibility and then select the method that best fits their specifications.
Users no longer have to rely on one method alone. Not only can information be
encrypted, it can be hidden altogether.
Greater amounts of information can be embedded without audible degradation.
Many attacks that are malicious against image Steganography algorithms (e.g.
geometrical distortions, spatial scaling, etc.) cannot be implemented against audio
Steganography schemes. Consequently, embedding information into audio seems
more secure due to less steganalysis techniques for attacking to audio.
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2. BACKGROUND STUDY
2.1 Literature Study
Literature study is basically done to understand the steganography, concept of Audio
steganography understanding content of a wave file. Literature study suggest some
algorithm which can be implemented to improve steganography response to attack.
2.1.1 Research paper study
Paper 1:
Title of paper-A study Of Steganography and Art of information Hiding
Authors-Alain C.Brainos II
Year of Publication-November 13, 2013
Publishing Details-East Carolina University
Summary
In this paper we understood the concept of Steganography. Steganography is technology
that hides the message within text, image, audio, video etc. Steganography is often
confused with the word cryptography. The easiest way to differentiate is the two is to
remember Steganography not only conceals content of message but also the mere
existence of message. Different approaches of steganography is explored. A new word
came into knowledge called Steganalysis. Steganalysis is a method to detect presence of
a hidden message and attempt to reveal the true content of the message. This paper
demonstrate various components of steganography which is mentioned in the report. The
Paper explores set of rules implemented to preserve intended results which is non visible
secret message with a cover data. Paper explains application of steganography in defense,
government purpose etc.
Paper 2:
Title of paper-Techniques of Data Hiding
Authors- W Bender, A Lu, D Gruhi
Year of Publication-1996
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Publishing Details-IBM System journal, vol 35, NOS 3 & 4
Summary
In this paper, several techniques are discussed as possible methods for embedding data in
host text, image, and audio signals. While we have had some degree of success, all of the
proposed methods have limitations. The goal of achieving protection of large amounts of
embedded data against intentional attempts at removal may be unobtainable. Automatic
detection of geometric and non-geometric modifications applied to the host signal after
data hiding is a key data-hiding technology. The optimum trade-offs between bit rate,
robustness, and perceivability need to be defined experimentally. The interaction between
various data-hiding technologies needs to be better understood. While compression of
image and audio content continues to reduce the necessary bandwidth associated with
image and audio content, the need for a better contextual description of that content is
increasing. Despite its current shortcomings, data-hiding technology is important as a
carrier of these descriptions.
Paper 3:
Title of paper-On the limits of Steganography
Authors- Ross J Anderson, Fabien
Year of Publication-May 1998
Publishing Details- IEEE journal of selected Area of communication
Summary
This paper explored the limits of steganographic theory and practice. We started outlining
a number of techniques both ancient and modern, together with attacks on them (some
new); we then discussed a number of possible approaches to a theory of the subject. We
pointed out the difficulties that stand in the way of a theory of perfect covertness" with
the same power as Shannon's theory of perfect secrecy. But considerations of entropy give
us some quantitative leverage and the selection channel the bandwidth of the stego key
led us to suggest embedding information in parity checks rather than in the data directly.
This approach gives improved efficiency, and also allows us to do public key
steganography. Finally, we have shown that public key steganography may be possible in
the presence of an active warden.
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Paper 4:
Title of paper-Performance improving LSB audio steganography
Authors- Burate D.J, M.R Dixit
Year of Publication- Volume 1, Issue 4, September 2013
Publishing Details- International Journal of Advance Research in Computer Science
Summary
The proposed method is improved version of the LSB technique used as audio
steganography, combined with coding technique gives high embedding capacity with
reference to literature survey LSB technique gives best results hence considered for
implementation. The present steganography techniques take help of well-known
cryptography algorithm to increase security level. But our proposed method uses other
coding technique. The message to be embedded is first converted to decimal then
converted to binary. After words it is converted to matrix whose rows are equal to total
no of character to be embedded. Then that matrix is converted to column matrix. And then
each bit is embedded into LSB of each audio sample. When embedding the textual
information in any audio file, first the audio signal is converted into bits. Then the
message to be embedded is converted from above strategy. By applying LSB algorithm,
the message is embedded into audio sample read at 16 bit format.
2.1.2 Integrated Summary of Literature
Before going deep into the steganography process, first and foremost, we need to
understand the various components of a steganography message. The below list covers
all the possible components that will be present in the steganography message.
Secret message: - refers to the part of the message which is intended to be hidden. This
message will later be encrypted to make it even more difficult for anyone who tries to
break the security to get hold of the hidden information message. This is the crucial
component in a steganography message.
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Cover Data (music file):-This component refers to the container in which the secret
message is hidden. This cover data component can be anything like digital photos, digital
videos, audio files and text files.
Stego message: - which is as crucial as the secret message. The stego message component
refers to the final product after hiding message in audio file.
2.1.1.2 Methods used audio Steganography
There are many encoding methods for performing audio steganography. The three of the
most popular encoding methods for hiding data inside of an audio file are:
Low-bit coding
Phase coding
Spread spectrum
2.1.1.2.1 Low-bit coding
Low-bit coding embeds secret data into the Least Significant Bit (LSB) of the audio file.
The channel capacity in this encoding method is 1 KB per second per Kilohertz. This
method is easy to incorporate but is very susceptible to data loss due to channel noise and
resampling .This method of 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, Low-bit coding allows for a large amount of data to be encoded. Figure.1
illustrates the message ‘HEY’ encoded as a 16-bit quality sample using the LSB method.
To extract a secret message from an LSB encoded sound file, the receiver needs
access to the sequence of sample indices used in the embedding process. Normally, the
length of the secret message to be encoded is smaller than the total number of samples in
a sound file. One trivial technique is to start at the beginning of the sound file and perform
LSB coding until the message has been completely embedded, leaving the remaining
samples unchanged
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Figure 1
2.1.1.2 Phase coding
Phase coding substitutes the phase of an initial audio segment with a reference phase that
represents the hidden data. This can be thought of, as sort of an encryption for the audio
signal by using what is known as Discrete Fourier Transform (DFT), which is nothing
more than a transformation algorithm for the audio signal. Phase coding addresses the
disadvantages of the noise-inducing methods of audio steganography.
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. Figure 2
given below illustrates the difference between the original signal and the encoded signal
after applying phase coding.
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Figure 2
In phase coding, the original sound signal is broken up into smaller segments whose lengths
equal the size of the message to be encoded. After this step, A Discrete Fourier Transform is
applied to each segment to create a matrix of the phases and Fourier transform
magnitudes. Once the matrix is created, phase differences between adjacent segments are
calculated.
After the phase differences were calculated, a new phase matrix is created using the new
phase of the first segment and the original phase differences. The final step is to
reconstruct the sound signal using the new phase matrix and original magnitude matrix
by applying the inverse DFT and then concatenate the sound segments back together.
To extract the secret message from the sound file, the receiver must know the segment
length. The receiver can then use the DFT to get the phases and extract the information.
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.
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2.1.2.3 Spread spectrum
The spread spectrum method encodes the audio over almost the entire frequency
spectrum. It then transmits the audio over different frequencies which will vary
depending on what spread spectrum method is used. Spread spectrum encoding
techniques are the most secure means by which to send hidden messages in audio, but
it can introduce random noise to the audio thus creating the chance of data loss. Spread
Spectrum is one of the audio steganography methods that analyze the frequency
masking threshold with the help of a psycho acoustic model [Matsuoka 2006]. This
model helps in embedding the spread signal in the audio just below the frequency
masking threshold. The spread spectrum audio steganography reduces the error
probability by increasing the spreading rate and coding gain.
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3. ANALYSIS, DESIGN AND IMPLEMENTATION
3.1 Requirement Specification
Software Requirements:
Front end – ASP.NET
Tool Kit – MS Visual Studio
Hardware Requirements:
Operating System – Windows XP or higher
HDD Space – 1 GB
RAM – 1 GB
Packages Requirements:
Basically to implement window media player following pre-defined packages are to be
included in application resources.
3.2 Functional and Non-Functional Requirements
Functional Requirements
Some of the Non-functional requirements of the project are as follows:
The system should select the correct file for encryption and decryption.
The system is supposed to perform steganography algorithm.
The system should encode the message without any loss of data.
The system should recover the data without losing its actual content.
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Should show and save decrypted text.
Should have an option to exit application.
Clear the space for new encryption.
Non-Functional Requirements
Some of the Non-functional requirements of the project are as follows:
User Privacy: Our project is confined with the policy of Data Hiding. While
hiding, we need to hide message in audio file so that there is no distortion in audio
file.
Response Time: There should be a timeout error since embedding and extracting
process takes negligible time.
Reliability: The system shall be able to provide the minimum level of precision.
The embedded wav file should be reliable to play on any system.
Maintainability: System is easy to maintain, unless there is a problem in the
version of the window or visual studio.
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3.3 Design diagram
3.3.1 Class Diagram
Figure 3
Encrypt
Encode
Save
Decode
Decrypt
Audio and
data
file/message
User
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3.3.2 Data Flow Diagram
Figure 4
Audio Steganography
User
User
User
User
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3.3.3.1 Activity Diagram (Embedding)
Figure 5
Get the data file
Exit
Get carrier file
Type the key
Validate
Encrypt and encode
Key ok
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3.3.3.2 Activity diagram (Extraction)
Figure 6
Get the source file
Exit
Type the key
Validate
Error message
invalid key Decrypt and Decode
Key ok Invalid key
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3.4 Risk Analysis and Mitigation Plan
Before executing a plan, it is very important to check the feasibility of that plan. Likewise
in software development is important to analysis the possible risks in a project.
Table 1
Risk
ID
Classification Description Risk
Area
Probability(P) Impact(I) RE(P*I)
1 Type 3 Identification
Of embedded
Audio file
Logical low(1) High(5) 5
2 Type 5 The app may
have some
errors while
running
Software Medium(3) High(5) 15
3 Type 4 Default
package may
change
Project
Scope
Medium(3) High(5) 15
4 Type 1 The machine
Response
time is large
Hardware Medium(3) High(5) 15
5 Type 1 The machine
may not be
able to meet
the hardware
requirements
of the
software
Hardware Low(1) High(5) 5
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Figure 7
Table 2
Risk Statement Risk Area Priority of Risk
Area in IG
Mitigation Plan
Erroneous Code Software 2 Test Code at every
stage
Identification of
Embedded File
Change in default
package
Erroneous
code
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4. IMPLEMENTATION AND TESTING
4.1 Implementation and Issue details
Embedding process 1. Select the audio file.
2. Make copy of audio file.
3. Input Key and Text message.
4. Convert the text into binary bit and forms coded text by coding it as described above
5. Read WAV audio file as cover file find header and total count size.
6. Find size of message, if size of message is more than count size, display message
’message is too big’ select small message.
7. Select audio sample and first hide key and then converted code of the text in WAV
file using LSB algorithm.
8. Repeat the above step still the whole message will be embedded in audio.
Extracting process
1. Read the stego file i.e. covers audio after embedding.
2. Extract the message by reading LSB.
3. Extract key from audio samples if key matches then extract hidden message otherwise
display message as ‘no message is hidden’.
4. Select all samples and store all LSB position bits in array.
5. Divide the array into number of rows and columns, convert binary hex and then into
ASCII character.
6. Display the secret message.
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Summary of application using diagram
Figure 8
Snapshot of working module
1. Login to start application
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2. Click embed button to embed message
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4.2 Testing
4.2.1 Testing Plan
S.
No.
Type of
Test
Will Test
be
Performed
?
Comments/Explanations Software
Components
1
Requirement
s
Testing
Yes This testing is required because we
need to verify whether our
requirements are able to solve the
current problem or not
Complete
Software
including GUI
2 Unit Testing Yes This testing allows us to test individual
modules before integrating them
together to form a single software
Data
Pre-processing
3 Integration Yes This test is important to check whether
the modules are giving the same
results after integrating as before
All Adjacent
Modules
4 Performance Yes This test is important to calculate the
efficiency of the software also helps us
to find any performance issue related
to the system
All the software
components
individually
5 Security Yes We have performed this test to Check
whether privacy is maintained.
Wave Data
7 Volume Yes We have performed this test to judge
the embedding in a better way.
Wave Data pre-
processing
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8 Compliance Yes This test is performed in order to check
whether we are implementing and
meeting the defined standards
GUI Components
Table 3
4.2.2 Component Decomposition & Type of Testing Required
S. No
Various Components that
require testing
Type of Testing
Required
Technique for
Writing Test Cases
1 Data Pre-processing Unit
Performance
Volume
Black Box
2 Data Embedding Unit
Performance
Volume
White Box
3 GUI Compliance Black Box
Table 4
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4.2.3 List of all test Cases
S. No
Test Case Id Input Expected
Output
Status
1 WAVE1
Wave file New wave file Pass
2 WAVE2 New wave file Encoded wave
file
Pass
3 WAVE3 Wave file Extracted data Pass
Table 5
4.2.4 Limitations of the solution
After all the testing and analysis of the project, following limitations were found:
Language Specific: This project is C# based hence requires application which can
implement asp based coding.
Extension File:This project can take only .wav file as input not mp3 or other files
as input content of data.
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5. Findings and Conclusion
5.1 Findings
After successful execution of project, we found that this project can be used for transmission
of large data sets without getting tracked by government, defence personals, corporate
business units
5.2 Conclusion
This report has looked in detail at the major techniques used for data hiding in audio files.
Section I gave an overview of Steganography and in particular the concept of Audio
Steganography. Section II described in detail, various Audio Steganography algorithms
namely LSB Coding, Phase Coding and Spread Spectrum. At the end, feasibility of Audio
Steganography was evaluated by considering it’s the pros and cons.
In summary, if implemented correctly SteganoSense can be best tool for data hiding.
5.3 Future Work
SteganoSense tool can be extended to make it work on Video file format and
other formats like 3GP, AVI etc.
At present, Wave audio files that are of PCM audio format works with
SteganoSense tool. Other audio formats require some form of compression.
This can be solved in future work.
Instead of LSB, Spread Spectrum method or phase coding method can be used
to insert secret message bits.
This application can be converted to Mobile Application
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Appendix-A
Gantt chart:
Phase 1: Project initiation and Requirement gathering
Phase 2: Planning, Estimating and Scheduling
Phase 3: Modeling, Analysis and Design
Phase 4: Coding and Unit testing
Phase 5: Component integration and System testing
Fig
X-axis denotes time in weeks.
0 2 4 6 8
Phase 5
Phase 4
Phase 3
Phase 2
Phase 1
37
Appendix-B
References
[Anderson, Petitcolas 1998] On the Limits of Steganography. IEEE Journal on
Selected Areas in Communications, Vol. 16, No. 4, May 1998. IEEE
[Bender 1996]. Techniques for Data Hiding, IBM system Journal, Pgs 313-336.
[Brainos II 2003] Brainos II, A. C. A Study of Steganography And The Art of Hiding
Information, East Carolina University, November 13, 2003.
[Howden 1987] William E. Howden. Functional program Testing and Analysis.
McGraw-Hill,1987.
[Burate 2013 ]Performance improving LSB audio steganography.
[ Md Ehmer Khan 2012] A comparative Study of White Box, Black Box and Grey
Box Testing Techniques. IJACSA Vol 3,No 6.
38
CURRICULUM VITAE
Rajan Yadav
Mo. No.: 8587909049
Email ID: [email protected]
Career Objective:
To achieve high carrier growth through a continuous learning process and keep myself dynamic, visionary
and competitive with the changing scenario of the world.
Educational Qualification:
Qualification Institute Board Year Of Passing %Marks
B. Tech (CSE) J.I.I.T Deemed
University
2011-2015 6.9 CGPA
Intermediate S.C.A.M Public
School
C.B.S.E 2010 75.03%
High School Nirmala Convent
School
C.B.S.E 2008 84.1%
CURRENTLY IN 8th SEMESTER OF B.TECH [CSE] FROM JIIT UNIVERSITY.
CGPA: 6.9/10 which is equivalent to 75% as per conversion table, approved by the academic council of
the university.
Technical Skill Sets:
LANGUAGES: C, Core Java.
TOOLS: Net Beans IDE, Rational Rose, Adobe Photoshop, Visual Studio.
39
Projects:
Software on College Management Systems (Aug. 2013 – Dec. 2013)
Successfully architected and developed a software using VB.Net.
Developed various modules like teacher/student/admin portal, time table, marksheet,
registration.
Software on Electronic Voting Machine (Aug. 2014 – Dec. 2014)
A multipurpose e-voting software that can be used at different levels and organizations.
Industrial Training:
Trainee at NTPC (National Thermal Power Corporation), Vidyut Nagar Dadri in “Networking”.
Certification:
Oracle Certified Professional (OCP), Java SE 6 Programmer.
Extra-Curricular Activities:
Actively participated in the College’s Annual Fest.
Attended “Basic Internet and Cyber Security” workshop on 3rd May 2014.
Participated in plays, debates and quizzes at school level.
Hobbies:
Football, Listening Music, Travelling.
Strength:
Confident, Optimistic, Interactive & always ready to learn.
Good in analytical skills, Excellent track record in college.
Always owned with “Can-Do-Spirit”.
Interested in updating knowledge through continuous learning.