a gray-scale image steganography technique using...
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A GRAY-SCALE IMAGE STEGANOGRAPHY TECHNIQUE USING
FIBONACCI 12-BITPLANE DECOMPOSITION AND LSB APPROACH
SABAH FADHEL HAMOOD
A dissertation submitted in partial fulfillment of the
requirements for the award of the degree of
Master of Science (Computer Science)
Faculty of Computing
Universiti Teknologi Malaysia
FEBRUARY 2013
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This dissertation is dedicated to my family for their endless support and encouragement.
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ACKNOWLEDGEMENT
First and foremost, I would like to express heartfelt gratitude to my supervisor
Prof. Dr. Ghazali Bin Sulong for his constant support during my study at UTM. He
inspired me greatly to work in this project. His willingness to motivate me contributed
tremendously to our project. I have learned a lot from him and I am fortunate to have
him as my mentor and supervisor
Besides, I would like to thank the authority of Universiti Teknologi Malaysia
(UTM) for providing me with a good environment and facilities such as Computer
laboratory to complete this project with software which I need during process.
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ABSTRACT
After the great expansion of internet, communications tends to be lifeblood, at
the same time data protection became more critical issue, so the need to secure transfer
channel is being more urgent, this goal achieved by applying one or more of data
protection techniques. Steganography one of the most suitable solution for this problem,
due to the good specification of concealing secret file inside cover image, in such way
there is nobody even suspects the existence of transferred file. The main challenge in
steganography methods is how to make balance between the quality of file that will be
used to conceal the secret and the size of the secret file. Also there are another factors
should be considered, which are, robustness and security against attacks. In this study
Fibonacci numbers have been exploited to achieve these goals. Fibonacci numbers used
to decompose the cover file into 12-bitplanes instead of 8-bitplanes produced by binary
decomposition, the four extra layers will increase the capacity of cover image. The
resulted 12-bitplanes, has special statistical nature in terms of distribution of black
regions (zero values) and white regions (one values). This statistical nature has been
exploited by modifying the binary representation of secret message to make matching
between the representation of secret message and cover image to reduce the impact of
embedding process on the resulted file (stego-image). By applying Fibonacci
decomposition to the cover image, better results have been achieved in terms of Peak
Signal to Noise Ratio(PSNR) which indicates the ability of embed more secret size with
maintaining the quality of stego-image, also the security and robustness has been
evaluated by applying chi-square attack, the result for this attacks show that Fibonacci
LSB method is withstanding for such attack.
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ABSTRAK
Selepas internet berkembang dengan pesatnya, komunikasi telah menjadi nadi, dalam
masa yang sama perlindungan data menjadi isu yang lebih kritikal, jadi keperluan untuk
mendapatkan saluran pemindahan menjadi lebih penting, matlamat ini dicapai dengan
menggunakan satu atau lebih teknik perlindungan data. Steganografi adalah salah satu
penyelesaian yang paling sesuai untuk masalah ini, disebabkan oleh penyembunyian fail
rahsia yang baik di dalam fail biasa (fail pelindung), dengan cara itu tiada siapa yang
akan mengesyaki walaupun fail dipindahkan. Cabaran utama dalam kaedah steganografi
adalah bagaimana untuk membuat keseimbangan antara kualiti fail yang akan digunakan
untuk menyembunyikan rahsia dan saiz fail rahsia tersebut. Juga terdapat faktor-faktor
lain yang perlu dipertimbangkan apabila teknik steganografi digunakan, faktor ini
adalah kekukuhan rahsia tersembunyi dan keselamatan penerapan teknik serangan yang
dijangka terhadap musuh. Untuk mencapai matlamat ini, nombor Fibonacci telah dikaji.
Nombor Fibonacci digunakan untuk menguraikan fail perlindungan ke 12-bitplanes
bukannya 8-bitplanes yang dihasilkan oleh penguraian binari, empat lapisan tambahan
akan membawa kepada peningkatan kapasiti fail perlindungan. Kesimpulan untuk 12-
bitplanes, mempunyai sifat statistik khas dari segi bentuk kawasan hitam (nilai sifar) dan
kawasan-kawasan putih (satu nilai). Sifat khas ini telah disalah guna dengan mengubah
sifat fail rahsia khas tersebut untuk membuat padanan antara sifat khusus fail rahsia dan
fail perlindungan dan untuk mengurangkan kesan proses penerapan pada fail akhir
(stego fail). Dengan menggunakan penguraian Fibonacci kepada imej penutup,
keputusan yang lebih baik telah dicapai dari segi Isyarat Puncak kepada Nisbah Bunyi
(PSNR).
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TABLE OF CONTENT
CHAPTER TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGMENT iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES xi
LIST OF FIGURES xiii
LIST OF ABBREVIATIONS xvi
1 INTRODUCTION
1.1 Introduction 1
1.2 Background of the Problem 3
1.2.1 Low Payload Capacity 3
1.2.2 Imperceptibility problems 4
1.2.3 Robustness Problem 4
1.3 Statement of the Problem 5
1.4 Research Aim 6
1.5 Objectives of Research 6
1.6 Research Scope 7
1.7 Significance of the Research 11
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2 LITERATURE REVIEW
2.1 Introduction 9
2.2 Historical Overview 10
2.3 Cryptography 11
2.4 Cryptography Vs Steganography 12
2.5 Combination of Crypto-Steganography 13
2.6 Steganography protocols 14
2.7 Digital Watermarking 15
2.7.1 Steganography and DigitalWatermarking 16
2.8 Types of steganography
2.8.1 Text Steganography 18
2.8.2 Image Steganography 19
2.8.3 Audio Steganography 20
2.8.4 Video Steganography 20
2.8.5 Protocol Steganography 21
2.9 Steganography terminology 21
2.10 Steganography properties 22
2.10.1 Imperceptibility 22
2.10.2 Robustness 23
2.10.3 Payload Capacity 24
2.11 Techniques of Steganography 24
2.11.1 Least Significant Bit (LSB) 26
2.11.2 LSB and Palette Based Images 28
2.11.3 Enhanced LSB Algorithms 29
2.11.3.1 SLSB Algorithm 29
2.11.3.2 The PVD Method 31
2.11.3.3 Applyingrandomizationconcepts to LSB 31
2.12 PSNR formula 35
2.13 Attacks on Steganography 36
2.14 Visual Attacks 37
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2.14.1 Statistical analysis of pairs ofvalues(histogram analysis) 38
2.14.2 Chi-square Attack 38
3 RESEARCH METHODOLOGY
3.1 Introduction 43
3.2 Dataset 44
3.3 Methodology 45
3.4 Data preparation 46
3.4.1 Cover Image Fibonacci Representation 47
3.4.2 Statistical Properties for Cover Image 49
3.4.3 Zeckendorf’s theorem 53
3.4.4 Pixels Decomposition using Fibonacci 54
3.4.5 Secret message preparation 57
3.5 Embedding Process 65
3.6 Imperceptibility Evaluation 69
3.7 Chi-square (χ2) Attack Implementation 69
3.8 Extraction Process 71
4 RESULTS AND DISCUSSION
4.1 Introduction 73
4.2 Implementation Results 74
4.2.1 Imperceptibility 74
4.2.1.1 PSNR Results 75
4.2.2 Visual Attack 81
4.2.3 Robustness Evaluation 85
4.3 Summary 88
5 CONCLOSIONS
5.1 Introduction 89
5.2 Work summary 90
5.3 Research Contribution 90
5.4 Future Works 91
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REFERENCES 93
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LIST OF TABLES
TABLE NO. TITLE PAGE
2.1 Comparison between Steganography and Cryptography 12
2.2 Comparison between steganography and digitalwatermarking. 17
2.3 LSB Insertion for Colored Image Pixel 30
2.4 The values of colored image pixel in SLSB Insertionmethod 30
2.5 Summary of Steganography techniques applied by differentauthors. 33
2.6 The values of Binary and Fibonacci system for some of nvalues 40
2.7 The maximum number of changing in pixel value afterembedding 40
3.1 Impact of each Fibonacci bitplane into whole image 47
3.2 Impact of each Binary bitplane into the whole image 48
3.3 Comparisons between 0’s and 1’s pixels value in bitplane(1) for binary representation 49
3.4 Fibonacci decomposition comparisons between 0’s and 1’spixels value in bitplane (1) 50
3.5 Binary decomposition comparisons between 0’s and 1’spixels value in bitplane (2) 51
3.6 Fibonacci decomposition comparisons between 0’s and 1’spixels value in bitplane (2) 52
3.7 The decimal and binary representation for lower case letterand whitespace 56
3.8 modified decimal and binary representation for lower caseletters 60
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4.1 The PSNR of Lena 512x512 pixel cover image afterembedding variable size payloads 76
4.2 The PSNR of Peppers 512x512 pixel cover image afterembedding variable size payloads 76
4.3 The PSNR of Camerman 512x512 pixel cover image afterembedding variable size payloads 77
4.4 The PSNR of Baboon 512x512 pixel cover image afterembedding variable size payloads 77
4.5 The PSNR of Lake 512x512 pixel cover image afterembedding variable size payloads 78
4.6 The PSNR of Pirate 512x512 pixel cover image afterembedding variable size payloads 78
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LIST OF FIGURES
FIGURE NO. TITLE PAGE
2.1 Cryptography steganography combination 13
2.2 Steganography category 18
2.3 General steganography system 22
2.4 Categories of image Steganography 25
2.5 Model of steganography and steganalysis 37
2.6 Shows the Binary Representation for 256Grayscale image 41
2.7 Shows the Fibonacci Representation for 256 ]Grayscale image 41
3.1 Grayscale images, (a) Peppers, (b) Baboon,(c) Lena, (d) Cameraman, (e) Lake, (f) Pirate 44
3.2 Operational Framework 45
3.3 Lena image with Fibonacci decomposition(12-Bitplane) 47
3.4 Lena image with Binary decomposition(8-Bitplane) 48
3.5 The probability of changing and not changingdue to embedding process into bitplane(1) 58
3.6 The probability of changing and not changingdue to embedding process into bitplane(2) 59
3.7 The probability of changing and not changingdue to embedding process into bitplane(1) 62
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FIGURE NO. TITLE PAGE
3.8 The probability of changing and not changingdue to embedding process into bitplane(2) 63
3.9 Chosen of pixels (P1,P2,…,P8) to hide secret insideit
65
3.10 Fibonacci LSB Embedding process 66
4.1 Grayscale images, (a) Peppers, (b) Baboon,(c) Lena,(d) Cameraman, (e) Lake, (f) Pirate 75
4.2 PSNR(db) Vs Payload(Bytes) for simple LSB,Fibonacci and the proposed method 79
4.3 Imperceptibility after embedding of (65536 bytes)using (a) Original imag (b) Simple LSB(c) Fibonacci LSB (d)Proposed method. 80
4.4 Representation of Layer(1) for all of ( (a) original,(b) binary embedding stego-image, (c) FibonacciLSB stego-image and (d) proposed methodstego-image) for Lena Stego-image withembedding of 65536 bytes embedding variablesize payloads 81
4.5 Representation of Layer(2) for all of ( (a) original,(b) binary embedding embedding sego-image,(c) Fibonacci LSB stego-image and (d) proposedmethod stego -image) for Lena Stego-image withembedding of 65536 bytes 82
4.6 Representation of Layer(3) for all of ( (a) original,(b) binary embedding sego-image, (c) FibonacciLSB stego-image and (d) proposed methodstego-image) for Lena Stego-image withembedding of 65536 bytes. 83
4.7 Chi-square attack on original Lena image. 84
4.8 Chi-square attack on lena stego-image after imbedding of16384 bytes by using of simple LSB method. 85
4.9 Chi-square attack on lena stego-image afterimbedding of 16384 bytes by using of FibonacciLSB method. 86
4.10 Chi-square attack on lena stego-image after
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FIGURE NO. TITLE PAGE
embedding of16384 bytes using of proposed method 86
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LIST OF ABBREVATIONS
LSB Least significant Bit
HVS Human Visual System
PVD Pixel Value Differencing method
MBNS Multiple-Base Notational System
DCT Discrete Cosine Transform
XML Extensible Markup Language
JPEG Joint Photographic Expert Group
GIF Graphic Interchange Format
Bitmap image formatBmp
OSI Open Systems Interconnection
TCP/IP Internet protocol suite TCP/IP
HAD Human Audio System
PSNR peak signal to noise ratio
MSE Mean Square Error
SLSB Selected Least Significant Bit
PVD Pixel-Value Differencing
PRNG Pseudo-Random Number Generator
RGB Red Green Blue
CHAPTER 1
INTRODUCTION
1.1 Introduction
Several years ago, an issue which has preoccupied the attention and thinking
of a lot people especially, in the military and political fields, is the data hiding
technique for the confidentiality of their information. This is more crucial for the
Middle East region, because of unstable political situations. The Middle East, being
the center of the Islamic world plus possessing more than 60% of the world's oil
therefore, the concern to find secure ways to send information is very important.
Thus, there were always methods and secret means that were followed to sending
these secret data. After the expansion of internet applications, information sending
has become quick and easy. Parallel to that, hackers were easily uncovered and
intercepted the sent data (Khalaf and Sulaiman, 2011).
One method of providing more security to data is information hiding, which
is the field of securing communication using cryptography, the cryptography
approach deals with the encryption of data at the sender’s side and the decryption of
data at the receiver’s side. Steganography is also used for secret data transmission;
the main difference between steganography and cryptography is the suspicion factor.
When steganography and cryptography are implemented together, the level of
security will increase. Steganography makes the presence of the secret data appear
invisible to eavesdroppers such as, key loggers or harmful tracking cookies where the
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users’ keystrokes are monitored while entering password and personal information.
So, “Steganography, is the art and science of hiding information, in such a way that,
its presence cannot be detected” (Ramkumar and Akansu, 1999). Steganography
used for hiding and sending data apparently using innocuous carriers to conceal even
the existence of the secret message (Petitcolas et al., 1999). The goal of applying
steganography is to make message communications in such secure and completely
undetectable way (Provos and Honeyman, 2003),(Amin et al., 2003).
The techniques of data hiding embed the confidential data into a multimedia
file such as video, images or sounds. The suitable cover signal is the digital image,
due to their insensitivity to human visual system HVS(Mohamed et al., 2011). The
word steganography “comes from Greek; stegano, which means covered or secret
and –graphy means writing or drawing. Therefore, steganography literally means
“covered writing”(Ramkumar and Akansu, 1999).
Steganography was developed centuries ago, but in recent decades has been
studied on the consideration of it being one of the areas of science. Nowadays, most
information is electronically kept and at the same time, the information security has
become an essential issue. Steganography, beside cryptography can be applied to
increase information security. Steganography is a method of hiding a secret message
in a digital signal. In comparison to cryptography, the secret message or encrypted
secret message is embedded into a digital carrier signal before sending it through the
network, thus the existence of the secret message is unknown(Ramkumar and
Akansu, 1999).
The Steganography goal is to hide secret messages inside another harmless
message in a way to not allow hackers to even know that there is a secret message
present(Kekre et al., 2008). The LSB replacement/ LSB matching terminology has
been discussed by(Sharp, 2001). The algorithm of LSB substitution is the simplest
technique for secret message hiding in a carrier signal. The replacement of the least
significant bit (LSB) of each pixel by the bit stream of the encrypted message, is
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applied according to this technique. The authorized recipient can decipher the least
significant bit (LSB) of all pixel of the carrier signal using a pre-shared key to extract
the secret message. This method of embedding is imperceptible by the human visual
system (HVS), because only the least significant bit of pixels is replaced by the
secret bit. Therefore, the maximum capacity for this algorithm is only 1 bit for each
pixel(Kekre, et al., 2008).
1.2 Background of the Problem
Steganography is a branch of data hiding techniques, it is also considered as
the art of secret hiding inside a cover of a carrier signal(Petitcolas, et al., 1999)
,(Wang and Wang, 2004). There are two valuable factors in Steganography which
should be applied at all times, first one is the perceptibility impact of the secret
embedding process with regards to the imperceptibility of visual/statistical image
properties, while the other factor is the amount of embedded information that can be
embedded into the cover signal(Zhang and Wang, 2005). When the size of the secret
file is larger than usual, it should be divided into a sequence of segments after that,
these segments will be embedded into multiple cover images before sending but,
multiple images sending to the same destination will increase the suspicion factor, so
to solve this problem the capacity of the stego-image needs to be increased.
1.2.1 Low Payload Capacity
The two most famous algorithms in which the stego-image is highly
imperceptible and the capacity of embedding process is low, which are Pixel-Value
Differencing (PVD) (Wu et al., 2005) and Multiple-Base Notational System (MBNS)
(Zhang and Wang, 2005). The maximum of embedding capacity of these two
algorithms depend on the cover signal characteristics and it can be different for
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different cover signals. These two algorithms are based according to HVS. The total
numbers of bits that are embedded in each pixel depend on the pixel, if it is in
smooth or in edge area. The maximum embedding capacity is equal to 782,320 bits
using PVD algorithm when the cover signal (image) is (airplane), while, when the
MBNS algorithm is applied using (Man) as the cover image, the maximum
embedding capacity is equal to 740,000 bits. There is a fact in steganography
technique which is, there will be a trade-off between imperceptibility and payload
capacity in the stego-image, the ideal algorithm of Steganography is that, the
algorithm that gives imperceptibility with an acceptable level, without losing any of
the payload capacity.
1.2.2 Imperceptibility problems
Among the steganographic insertion techniques, there's an important issue,
which is the way of embedding a secret message into an 8-bit grayscale image,
(which will be considered as a cover signal) in such a technique that cannot be
detected by the human visual system (HVS) for the existence of this secret message,
without attention to the expected attack like, Chi-square Attack. Most important is
the way of getting acceptable imperceptibility and achieving bigger imperceptibility
is very important, even if more pixels are used for estimating the capacity for each
target pixel.
1.2.3 Robustness Problem
There is another steganographic property that should be considered when
steganographic techniques are applied, especially when the least significant bit (LSB)
technique is used, this property is known as robustness. The embedding algorithm
can be said to be robust if the embedding secret cannot be removed after applying a
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reliable detection by a targeted attack; when there’s full knowledge about the
detector, the embedding algorithm (except knowing the secret key), also the
knowledge of at least one carrier with the hidden secret(Michaud, 2003).
1.3 Statement of the Problem
The most famous steganography techniques are DCT and LSB. In first one,
the coefficient values of DCT of some image squares are changed for the process of
embedding the secret message(Johnson et al., 2001). Whereas, in the LSB technique
areas inside the cover image are selected by using different techniques, and then the
least significant bit is replaced with the data that needs to be embedded.
Using LSB technique with which this approach would be concerned, an
image is used to embed the secret data inside it, and then take the values of its gray-
scale. An alternation operation of the least significant bit of gray-scale can be easily
made and it is undetectable by the human visual system, HVS. So, a stego-image
with high imperceptibility will be achieved. Also, as mentioned in(Wang and Wang,
2004), there are some issues in steganography, the main effort for this study is to
increase the payload capacity by using Fibonacci sequences and also by using this
technique to get a high robustness stego-image. So the decreasing of image distortion
and imperceptibility will be considered.
Fibonacci sequences are related to Leonardo Pisano Fibonacci, who was born
around 1170 and died around 1250, in Pisa, what is now Italy. He was always
travelling in Northern Africa and Europe. Several mathematical notations were
written by him; also, he introduced Europe to the numbers of Hindu-Arabic
notations. Although his books were transcribed by the hand, they were circulated
widely. In one of most famous of his books, Liber Abaci, which was published in
1202, he proposed the following problem: A man puts a pair of rabbits in a place
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surrounded on all sides by a wall. How many pairs of rabbits can be produced from
that pair in a year if it is supposed that every month each pair begets a new pair
which from the second month on becomes productive?. Presently, the solution for
such problem is known as Fibonacci numbers, or Fibonacci sequence, also there is a
mathematical industry that is based on Fibonacci sequence. The internet search for
these sequences will match dozens of web sites, and hundreds of material pages
today for the solution to this problem. There is even a Fibonacci Association that
publishes a scholarly journal, which is Fibonacci Quarterly.
1.4 Research Aim
The main aim of this study is to improve a steganographic method which can
embed secret information into a cover image, with high payload capacity using
Fibonacci sequences to hide the data within the framework of adopting the classical
LSB scheme.
1.5 Objectives of Research
In order to achieve the aim of the study, there are some identified objectives,
such as follows:
To propose improved steganography algorithm based on Fibonacci LSB
technique to provide a high embedding capacity.
To make comparisons between classical LSB technique and Fibonacci-based
LSB technique and the proposed technique according to the payload
capacity and imperceptibility.
To evaluate the robustness of the proposed method against Chi-square attack.
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1.6 Research Scope
The proposed approach scope is based on the following points:
The secret message, which is embedded into the cover media will be
an arbitrary generated text with lower case letters (a to z) and space
(whitespace).
The cover media that is used for hiding the desired secret data is a
standard dataset of (512 x 512) pixels, and 8-bits gray-scale image
taken from the data base of USC-SIPI.
PSNR formula will be used to evaluate the imperceptibility of stego-
image in order to compare with previous works.
Chi-sqaure will be used to evaluate the robustness of the proposed
technique.
1.7 Significance of the Research
Due to the expansion in the field of Internet and wide dependence on the
internet resources, the World Wide Web has today become non secure in the transfer
of data, so the need to make this environment safer has become more urgent and to
achieve a secure environment, the implementation of some security technologies has
become valuable.
Steganography, being a more secure technology, has been applied to get a
secure communication channel between the sender and the receiver using internet as
a communication media. Since Steganography is under some vulnerability such as,
payload capacity is one of the most important factor in addition to the
imperceptibility of the stego-image.
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The proposed technique in this study tries to increase the payload capacity in
keeping with the imperceptibility at an acceptable level. This result can be achieved
by using least significant bit (LSB) insertion based on Fibonacci decomposition, the
insertion of secret bits into the (LSB) of Fibonacci representation is accomplished
after making a preprocessing for the secret bits to be adaptive for embedding into the
cover image with a minimum image distortion, to get a stego-image with high
capacity, without losing the imperceptibility.
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