arvind stegnography
TRANSCRIPT
CDGI’S
CHAMELI DEVI SCHOOL OF
ENGINEERING, INDORE
STEGANOGRAPHY
by
Arvind Carpenter
(0832CS121020)
Ms. Renu Dangi
(Academic staff)
DEPARTMENT OF COMPUTER SCIENCE
ENGINEERING EVEN SEMESTER 2015
CDGI’S
CHAMELI DEVI SCHOOL OF
ENGINEERING, INDORE
STEGANOGRAPHY
by
Arvind Carpenter
(0832CS121020)
Ms. Renu Dangi
(Academic staff)
DEPARTMENT OF COMPUTER SCIENCE
ENGINEERING EVEN SEMESTER 2015
CDGI’S
CHAMELI DEVI SCHOOL OF ENGINEERING, INDORE
DEPARTMENT OF COMPUTER SCIENCE ENGINEERING
EVEN SEMESTER 2015
CERTIFICATE
Certified that this is the bonafide record of the seminar report on
STEGNOGRAPHY Carried out by
Arvind Carpenter (0832CS121020)
of VI semester (Department of Computer Science Engineering) during the Odd Semester 2015. He has satisfactorily completed the seminar report and presentation as prescribed by the Rajiv Gandhi Technical University, Bhopal, in partial fulfillment towards the award of B.E. Degree in Computer Science Engineering.
Signature of Guide Signature of Seminar coordinator
(Name : Ms. Renu Dangi) (Name: )
Date: / /2015 Date: / /2015
Signature of HOD
(Name: Mr. Surendra Shukla)
Date: / /2015
ABSTRACT
We propose a new method for strengthening the security of information through a combination
of signal processing, cryptography and steganography. Cryptography provides the security by
concealing the contents and steganography provides security by concealing existence of
information being communicated. Signal processing adds additional security by compressing and
transforming the information. The proposed method, viz. Steganography Based Information
Protection Method (SBIPM), consists of scanning, coding, encryption, reshaping, cover
processing and embedding steps.
We then turn to data-hiding in images. Steganography in images has truly come of age with the
invention of fast, powerful computers. Software is readily available off the Internet for any user
to hide data inside images. These softwares are designed to fight illegal distribution of image
documents by stamping some recognisable feature into the image.The most popular technique is
Least Significant Bit insertion, which we will look at. Also, we look at more complex methods
such as masking and filtering, and algorithms and transformations, which offer the most
robustness to attack, such as the Patchwork method which exploits the human eye's weakness to
luminance variation.
We will take a brief look at steganalysis, the science of detecting hidden messages and
destroying them. We conclude by finding that steganography offers great potential for securing
of data copyright, and detection of infringers. Soon, through steganography,personal
messages,files, all artistic creations, pictures, and songs can be protected from piracy.
CDGI’S
CHAMELI DEVI SCHOOL OF ENGINEERING, INDORE
DEPARTMENT OF COMPUTER SCIENCE ENGINEERING
EVEN SEMESTER 2015
ACKNOWLEDGEMENT
I have immense pleasure in expressing my sincerest and deepest sense of
gratitude towards my Guide Ms. Renu Dangi (Acadmic staff) for the assistance
in preparing and presenting the seminar. I also take this opportunity to thank
Seminar Coordinator and Head of the department, for providing the required
facilities in completing my seminar report.
I am greatly thankful to my Parents, Friends and Faculty members for their
motivation, guidance and help whenever needed.
Arvind Carpenter
(0832CS121020)
Contents
Chapter No.
Description Page numbers.
Certificate I
Synopsis Ii
Acknowledgement Iii
Contents Iv-v
1 Introduction 01
2 Requirement 01
2.1 Capacity 01
2.2 Imperceptibility 02
2.3 Robustness 02
3 Steganography Vs Cryptography 02
4 Non Cyber Techniques In Steganography 02
4.1 Subset 02
4.2 Null Cipher 03
4.3 Baccon Cipher 04
5 Fingerprinting And Watermarking 05
6 Least Significant Bit Insertion 05
7 Public Key Steganography 06
8 Transform Domain Based Steganography 07
9 Steganography In Images 08
9.1 Abstract 08
9.2 Introduction 08
9.3 Kerckoff Principle 09
9.4 Steganography Diagrammatic Flow 09
10 Images 10
10.1 Image Compression 11
10.2 Image Encoding Techniques 12
10.2.1 LSB Insertion 12
10.2.2.1 Advantages Of LSB Insertion 12
10.2.2 Masking And Filtering 13
10.2.3 Algorithms And Transformations 13
11 System Design 14
12 Conclusion 14
13 References 15
List of Figures
Figure No. Title of Figure Page numbers.
1 Flow Chart 1
9.4 Overview 9
10.0 Image Compression 11
1 | P a g e
1. INTRODUCTION
Digital communication has become an essential part of infrastructure nowadays, a lot of
applications are Internet-based and in some cases it is desired that the communication be
made secret. Two techniques are available to achieve this goal: one is cryptography, where the
sender uses an encryption key to scramble the message, this scrambled message is transmitted
through the insecure public channel, and the reconstruction of the original, unencrypted
message is possible only if the receiver has the appropriate decryption key. The second
method is steganography, where the secret message is embedded in another message. Using
this technology even the fact that a secret is being transmitted has to be secret There are two
main directions in information hiding: protecting only against the detection of a secret
message by a passive adversary, and hiding data so that even an active adversary cannot
remove it. The classic situation, known as Simmons’ “Prisoners’ Problem”, is the following:
Alice and Bob are in jail and try to discuss an escape plan, but all their communication can be
observed by the warden. If their plan or the fact that they are discussing an escape plan were
detected they would be transferred to a more secure prison. So they can only succeed if Alice
can send messages to Bob so that the warden can’t even detect the presence of a secret .
There are a lot of real applications of steganography. For example during the 80s some
confidential cabinet documents were passed to the English press so Margaret Thatcher had the
word processors modified to encode the identity of the user into the word spacing of the
documents so the identity of an information source could be found out
2. REQUIREMENT
There are different requirements depending on the purpose of steganography:
1 Flow Chart
2 | P a g e
2.1 CAPACITY : It is an important factor in captioning applications, when a lot of
information should be embedded into a cover image, what is usually related to the current
picture. For example when transmitting medical images, the personal data, and the
diagnosis could be embedded into the same picture.
2.2 IMPERCEPTIBILITY: it is important when a secret communication occurs
between two parties and the fact of a secret communication is kept to be secret.
2.3 ROBUSTNESS: watermarking, fingerprinting and all copyright protecting
applications demand robust steganographic method, i.e. where the embedded information
cannot be removed without serious degradation of the image
Steganography embeds a secret message in a cover message, this process is usually
parameterized by a stego-key, and the detection or reading of an embedded information is
possible only having this key
3 STEGANOGRAPHY VS CRYPTOGRAPHY
3.1 STEGANOGRAPHY Embedding information (plaintext) within other seemingly harmless information (cover text) in
such a way that no one but the intended recipient would try to retrieve it.
3.2 CRYPTOGRAPHY transforming information (plaintext) into other unintelligible information (cipher text) such that
no one but the intended recipient would be able to retrieve it
3.3FURTHER DIFFERENCES
Steganography
– hide, without altering
– obfuscates the fact of communication, not the data
– preventative - deters attacks
Cryptography
– alter, without hiding
– obfuscates the data, not the fact of communication
– curative - defends attacks
3 | P a g e
4 NONCYBER TECHNIQUE IN STEGANOGRAPHY
4.1 SUBSET
Dear George;
Greetings to all at Oxford. Many thanks for your
letter and for the summer examination package.
All Entry Forms and Fees Forms should be ready
for final dispatch to the Syndicate by Friday
20th or at the very latest, I’m told by the 21st.
Admin has improved here, thought there’s room
for improvement still, just give us all two or three
more years and we’ll really show you! Please
don’t let these wretched 16+ proposals destroy
your basic O and A pattern. Certainly this
sort of change, if implemented immediately,
would bring chaos.
Sincerely yours;
Imagine a package is being prepared for you. This tells you when and where you can get it:
Dear George;
Greetings to all at Oxford. Many thanks for your
letter and for the summer examination package.
All Entry Forms and Fees Forms should be ready
for final dispatch to the Syndicate by Friday
20th or at the very latest, I’m told by the 21st.
Admin has improved here, thought there’s room
for improvement still, just give us all two or three
more years and we’ll really show you! Please
don’t let these wretched 16+ proposals destroy
your basic O and A pattern. Certainly this
sort of change, if, implemented immediately
would bring chaos.
Sincerely yours
11-word message in 93-word cover text (8.45 ratios – haystack to needle) cover text
plaintext
4.2 NULL CIPHER
PRESIDENT'S EMBARGO RULING SHOULD HAVE IMMEDIATE NOTICE. GRAVE SITUATION AFFECTING
4 | P a g e
INTERNATIONAL LAW. STATEMENT FORESHADOWS
RUIN OF MANY NEUTRALS. YELLOW JOURNALS
UNIFYING NATIONAL EXCITEMENT IMMENSELY.
PERSHING SAILS FROM NY JUNE I
-character message in 204-character cover text (8.50 ratio)
same plaintext APPARENTLY NEUTRAL'S PROTEST IS THOROUGHLY
DISCOUNTED AND IGNORED. ISMAN HARD HIT.
BLOCKAD
24E ISSUE AFFECTS PRETEXT FOR EMBARGO
ON BYPRODUCTS, EJECTING SUETS AND VEGETABLE
OILS.
PERSHING SAILS FROM NY JUNE I
24-character message in 176-character cover text (7.33 ratios)
B
4.3 BACCON CIPHER
H a v e f u n
aabbb aaaaa baabb aabaa aabab baabb abbaa
BUrgeR WITH fRIes TAsTY BUt Not FOr hEalTH
7-character message in 35-character cover text (5.00 ratio) uses a “bilateral” alphabet each
letter has 2 possible fonts (or cases)
his one? USc atHlETICS is SURpasSed BY ComPuTer ScIenCE Hint: starts with same letter as previous because BUrge == UScat
Doing it with computers Steganography – hiding a file inside of another – typically hiding text inside of a media file
– normally used for the transportation of secretive
information
Man _LSB CONTINEOUS
Idea is that the least significant bit of a byte can change with little change to the overall file
_ Consider a 8-bit grey scale image
5 | P a g e
– One pixel of information is stored using 8 bits.
– There are 256 different variations of grey.
1 0 0 1 0 1 1 0
_ Change in the LSB information of some area of the image will not be noticeable by naked eye.
_ Utilizing this fact the message is embedded
10101101 00101010 10100010 10010001 10…
10101100 00101011 10100011 10010000 10…
LSB advantages and
Advantages
– Does not change the size of the file
– Is harder to detect than other steganography techniques
Disadvantages
– Normally must use the original program to hide and reveal data
– If the picture with the hidden information is converted to another format, then the hidden data
may be lost
5. FINGERPRINTING AND WATERMARKING
so that one does not have to store distinctly the images, and connected information. When the
purpose is the protection of intellectual property, we can make a distinction between
fingerprinting and watermarking. In the case of watermarking copyright information is
embedded in a digital media, and this media is transmitted to users. Fingerprinting embeds
separate mark in the copies of digital media, this embedded information serves as a serial
number, and it can be detected who supplied this media to third parties. Nowadays
steganography is more and more important in publishing and broadcasting industries, where the
embedding of copyright marks or serial numbers is needed in digital films, photos and other
multimedia products. Some steganographic applications are able to scan the Internet, and to
detect a copy of a specific image, or the modified image is published – so an illegal usage of a
copyrighted image can be detected. In the case of audio materials, the automatic monitoring of
radio advertisements is also possible, the advertiser can automatically count how many times a
specific advertisement was transmitted by a given radio station. Another possible application in
the case of still images is to embed captions and other information into the picture
6. LEAST SIGNIFICANT BIT INSERTION
6 | P a g e
Usually 24-bit or 8-bit files are used to store digital images. The former one provides more space
for information hiding, however, it can be quite large. The colored representations of the pixels
are derived from three primary colors: red, green and blue. 24-bit images use 3 bytes for each
pixel, where each primary color is represented by 1 byte. Using 24-bit images each pixel can
represent 16,777,216 color values. We can use the lower two bits of these color channels to hide
data, then the maximum color change in a pixel could be of 64-color values, but this causes so
little change that is undetectable for the human vision system. This simple method is known as
Least Significant Bit insertion [4], [15]. Using this method it is possible to embed a significant
amount of information with no visible degradation of the cover image.
Several versions of LSB insertion exist. It is possible to use a random number generator
initialized with a stego-key and its output is combined with the input data, and this is embedded
to a cover image. For example in the presence of an active warden it is not enough to embed a
message in a known place (or in a known sequence of bits) because the warden is able to modify
these bits, even if he can’t decide whether there is a secret message or not, or he can’t read it
because it is encrypted. The usage of a stego-key is important, because the security of a
protection system should not be based on the secrecy of the algorithm itself, instead of the choice
of a secret key [11].
The LSB inserting usually operates on bitmap images. ‘Steganos for Win252
J. LENTI
Original (cover) pixel
Masked pixel:
Stego pixel:
Secret information:
R G B
R G B
DOWS’ and ‘WBSTEGO’ are LSB inserting software products which are able to embed data (in
clear or encrypted format) in a bitmap image. The embedded data cannot be considered as a
watermark, because even if a small change occurs in a picture (cropping, lossy compression, and
color degradation) the embedded information will be lost – although the change which is
occurred during the embedding process is invisible.
The original bitmap picture which was used during the test was a picture 1024 × 768 pixel in
size, with 16M colors (it is a standard test picture in image processing). We made a test using
bitmap images. The following pictures will STEGANOGRAPHIC METHODS 253 show the
results using different software with different embedded data size: original watch.bmp 100 kb
embedded information with ‘Steganos for Windows’ 200 kb embedded information with
‘wbstego’ the difference between the original and the modified (100 kb Steganos for Win.) the
difference between the original and the modified(200 kb wbstego)
When these pictures were modified all the embedded information was lost. These software’s do
not use any redundancies during embedding, the embedding process does not apply any error
correcting codes. In this case the error correction and the redundancies are useful only if the
image is modified in bmp format. If a lossy compression technique is applied, usually all the lsb
bits are lost, therefore all embedded information is also destroyed.
7 | P a g e
7. PUBLIC KEY STEGANOGRAPHY
As another possible way the algorithm requires the pre-existence of a shared secret key to
designate pixels which should be tweaked. In this case both the sender and the receiver must
have this secret. Suppose that the communicating parties do not have the opportunity to agree a
secret key, but one of them (e.g. Bob) has a private/public key pair, and his partner knows the
public key. In the case of a passive warden Alice knowing Bob’s public key encrypts her
message with this key, embeds it in a known channel (known position in the cover media), and
sends 254 J. LENTI it to Bob. Bob cannot be sure whether the channel contains a hidden
message, but he can try to decrypt the random-looking string-sequence with his private key, and
check whether it is a message or not [5].
Another approach is the cover image escrow scheme (or source extraction), where the extractor
is required with the original cover image, and the cover image is subtracted from the stego image
before the extraction of the embedded information.
In this scheme, the user cannot read the embedded data, it is only possible to have the original
unmodified picture, but these types of algorithms are characterized as robust against signal
distortions.
8. TRANSFORM DOMAIN BASED STEGANOGRAPHY
The destination extraction algorithms can be divided into two groups: spatial/time domain and
transform domain techniques. In the former case information is embedded in the spatial domain
in the case of images, and in time domain in the case of audio materials. The transform domain
methods operate in the Discrete Cosine Transform, Fourier or wavelet transform domains of the
host signal [2], [11], and [15].
The Patchwork algorithm (developed at the MIT) selects random pairs of pixels, and increases
the brightness of the brighter pixel and decreases the brightness of the other. This algorithm
shows a high resistance to most no geometric image modifications. If it is important to provide a
protection against filtering attacks, then the information hiding capacity is limited [4]. High color
quality images are compressed usually using a lossy compression method as, for example, in the
case of Jpeg images. In Jpeg algorithm the pixels are first transformed into a luminance-
chrominance space. The chrominance is then down sampled – it is possible because the HVS
(Human Vision System) is less sensitive to chrominance changes than to luminance changes – so
the volume of the data is reduced. Discrete Cosine Transform is then applied on the groups of 8
× 8 pixels. The next step causes the most loss in the case of Jpeg, where the coefficients are
scalarly quantized (it is possible because if we reduce the coefficients of higher frequencies to
zero, the changes to the original image will cause only small changes that a human viewer could
not detect under normal circumstances). The final steps are lossless, when these reduced
8 | P a g e
coefficients are also compressed and a header is added to the Jpeg image. (See a detailed
description in [5]). Steganographic applications usually operate after the quantization step, for
example Jpeg-Jsteg, and SysCoP. SysCoP uses a position sequence generator. The inputs of the
generator are the image data and user key, the output is a position sequence for selecting blocks
where the code is embedded [14], [2]. The block consists in this case of 8 × 8 pixels, it can be
contiguous – the block is a square in the image – or distributed, where the pixels are randomly
selected. A label bit is embedded through setting specific relationship among three quantized
elements of a block, and the algorithm contains a checking mechanism to test whether the actual
block is capable or not to store this information, how big STEGANOGRAPHIC METHODS 255
modification is needed to store one bit information among these pixels.
A popular method in a frequency domain is to modify the relative size of
two or more DCT coefficients in an image block, embedding one bit information in each block.
The two coefficients should correspond to cosine functions with middle frequencies which mean
that the information is stored in a significant part of the signal. The algorithm should be robust
against Jpeg compression, so the DCT coefficients with equal quantization values should be
chosen, according to the quantization table of Jpeg.
In the frequency domain the embedding process can usually hide less information into pictures,
there is not such an exact limit in the size of the embedded object as in the case of LSB insertion,
where the number of pixels, and the color depth determine the maximum size of the embedded
data (and it was sure, that the changes occurred during embedding will be invisible). In the case
of a transform domain operation the embedding process can cause visible changes if the
embedded data size is too big, and the limit where a given embedded data size does not change
the visual properties of the image is image dependent. The following figures show the result of
the embedding process in transform domain.
30 kb of embedded data
with ‘jhps’
50 kb of embedded data
with ‘jhps’
60 kb of embedded data
with ‘jhps’
In the case of a watch test picture 50 kb embedded data (and above) modifies the visible
properties of the image, so when the stego-image is compared with the original one it is possible
to recognize a modification.
9. STEGANOGRAPHY IN IMAGES
9.1 ABSTRACT: In this , we aim to present a general introduction to steganography or data-hiding as it is
sometimes just known. We then turn to data-hiding in images. When examining these data-
hiding techniques, we bear in mind Bender's specifications, such as degradation of the cover data
must be kept to a minimum, and the hidden data must be made as immune as possible to possible
attack from manipulation of the cover data. Steganography in images has truly come of age with
9 | P a g e
the invention of fast, powerful computers. Software is readily available off the Internet for any
user to hide data inside images. This software’s are designed to fight illegal distribution of image
documents by stamping some recognizable feature into the image. The most popular technique is
Least Significant Bit insertion, which we will look at. Also, we look at more complex methods
such as masking and filtering, and algorithms and transformations, which offer the most
robustness to attack, such as the Patchwork method which exploits the human eye's weakness to
luminance variation. we will take a brief look at steganalysis, the science of detecting hidden
messages and destroying them. We conclude by finding that steganography offers great potential
for securing of data copyright, and detection of infringers. Soon, through steganography,personal
messages, files, all artistic creations, pictures, and songs can be protected from piracy
9.2 INTRODUCTION:
Steganography, from the Greek, means covered, or secret writing, and is a long-practiced form of
hiding information. Although related to cryptography, they are not the same. Steganography's
intent is to hide the existence of the message, while cryptography scrambles a message so that it
cannot be understood. More precisely,
``the goal of steganography is to hide messages inside other harmless messages in a way that
does not allow any enemy to even detect that there is a second secret message present.''
Steganography includes a vast array of techniques for hiding messages in a variety of media.
Among these methods are invisible inks, microdots, digital signatures, covert channels and
spread-spectrum communications. Today, thanks to modern technology, steganography is used
on text, images, sound, signals, and more. In the following sections we will try to show how
steganography can and is being used
through the media of images.
9.3 KERCKOFF PRINCIPLE:
In cryptography. This principle states that “the security of the system has to be based on the
assumption that the enemy has full knowledge of the design and implementation details of the
steganographic system”. The only missing information for the enemy is a short, easily
exchangeable random number sequence, the secret key.
9.4 STEGANOGRAPHY DIAGRAMATIC FLOW:
10 | P a g e
Information to be
hidden
Stego tool
Law enforcement may
intercept but doesn’t know
that document is hidden
Hidden
document
internet
Stego tool
When embedding data, it is important to remember the following restrictions and features:
cover data should not be significantly degraded by the embedded data, and the embedded
data should be as imperceptible as possible. (This does not mean the embedded data needs to be
invisible; it is possible for the data to be hidden while it remains in plain sight.)
wrapper, to maintain data consistency across formats.
or anticipated manipulations such as filtering and resembling.
modified. To minimize this, error correcting codes should be used.
11 | P a g e
-clocking or arbitrarily re-entrant. This ensures that the
embedded data can still be extracted when only portions of the cover data are available. For
example, if only a part of image is available, the embedded data should still be recoverable.
User can get the hidden information using password
In this section we deal with data encoding in still digital images. In essence, image
steganography is about exploiting the limited powers of the human visual system (HVS).
Within reason, any plain text, cipher text, other images, or anything that can be embedded in a
bit stream can be hidden in an image. Image steganography has come quite far in recent years
with the development of fast, powerful graphical computers, and steganographic software is now
readily available over the Internet for everyday users.
10. IMAGES:
To a computer, an image is an array of numbers that represent light intensities at various points,
or pixels. These pixels make up the image's raster data. An image size of 640 by 480 pixels,
utilizing 256 colors (8 bits per pixel) is fairly common. Such an image would contain around 300
kilobits of data. Digital images are typically stored in either 24-bit or 8-bit per pixel files. 24-bit
images are sometimes known as true color images. Obviously, a 24-bit image provides more
space for hiding information; however, 24-bit images are generally large and not that common. A
24-bit image 1024 pixels wide by 768 pixels high would have a size in excess of 2 megabytes.
As such, large files would attract attention were they to be transmitted across a network or the
Internet. Image compression is desirable. However, compression brings with it other problems
that shall be explained shortly.
Alternatively, 8-bit color images can be used to hide information. In 8-bit color images, (such as
GIF files), each pixel is represented as a single byte. Each pixel merely points to a color index
table, or palette, with 256 possible colors. The pixel's value, then, is between 0 and 255. The
image software merely needs to paint the indicated color on the screen at the selected pixel
position. If using an 8-bit image as the cover-image, many steganography experts recommend
using images featuring 256 shades of gray as the palette, for reasons that will become apparent.
Grey-scale images are preferred because the shades change very gradually between palette
entries. This increases the image's ability to hide information. When dealing with 8-bit images,
the steganographer will need to consider the image as well as the palette. Obviously, an image
with large areas of solid color is a poor choice, as variances created by embedded data might be
noticeable. Once a suitable cover image has been selected, an image encoding technique needs
to be chosen.
10.1 IMAGE COMPRESSION:
12 | P a g e
Image compression offers a solution to large image files. Two kinds of image compression are
lossless and lossy compression. Both methods save storage space but have differing effects on
any uncompressed hidden data in the image. Lossy compression, as typified by JPEG (Joint
Photographic Experts Group) format files, offers high compression, but may not maintain the
original image's integrity. This can impact negatively on any hidden data in the image. This is
due to the lossy compression algorithm, which may ``lose'' unnecessary image data, providing a
close approximation to high-quality digital images, but not an exact duplicate. Hence, the
term``lossy'' compression. Lossy compression is frequently used on true-color images, as it
offers high compression rates.
Lossless compression maintains the original image data exactly; hence it is preferred when the
original information must remain intact. It is thus more favored by steganographic techniques.
Unfortunately, lossless compression does not offer such high compression rates as lossy
compression. Typical examples of lossless compression formats are CompuServe’s GI(Graphics
Interchange Format) and Microsoft's BMP (Bitmap) format.
10.2 IMAGE ENCODING TECHNIQUES:
Information can be hidden many different ways in images. Straight message insertion can be
done, which will simply encode every bit of information in the image. More complex encoding
10.0 Image Compression
13 | P a g e
can be done to embed the message only in ``noisy'' areas of the image that will attract less
attention. The message may also be scattered randomly throughout the cover image.
.
The most common approaches to information hiding in images are:
Each of these can be applied to various images, with varying degrees of success. Each of them
suffers to varying degrees from operations performed on images, such as cropping, or resolution
decrementing, or decreases in the color depth.
10.2.1 EAST SIGNIFICANT BIT INSERTION:
One of the most common techniques used in steganography today is called least significant bit
(LSB) insertion. This method is exactly what it sounds like; the least significant bits of the cover-
image are altered so that they form the embedded information. The following example shows
how the letter A can be hidden in the first eight bytes of three pixels in a 24-bit image.
Pixels: (00100111 11101001 11001000)
(00100111 11001000 11101001)
(11001000 00100111 11101001)
A: 10000001
Result: (00100111 11101000 11001000)
(00100110 11001000 11101000)
(11001000 00100111 11101001)
The three underlined bits are the only three bits that were actually altered. LSB insertion requires
on average that only half the bits in an image be changed. Since the 8-bit letter A only requires
eight bytes to hide it in, the ninth byte of the three pixels can be used to hide the next character of
the hidden message. A slight variation of this technique allows for embedding the message in
two or more of the least significant bits per byte. This increases the hidden information capacity
of the cover-object, but the cover-object degrades more statistically, and it is more detectable.
Other variations on this technique include ensuring that statistical changes in the image do not
occur. Some intelligent software also checks for areas that are made up of one solid color.
Changes in these pixels are then avoided because slight changes would cause noticeable
variations in the area.
10.2.1.1 Advantages of LSB Insertion:
LSB color
alterations via palette manipulation.
-scale images.
14 | P a g e
least significant bits per byte. This increases the hidden information capacity
10.2.2 Masking and filtering :
Masking and filtering techniques hide information by marking an image in a manner similar to
paper watermarks. Because watermarking techniques are more integrated into the image, they
may be applied without fear of image destruction from lossy compression. By covering, or
masking a faint but perceptible signal with another to make the first non-perceptible, we exploit
the fact that the human visual system cannot detect slight changes in certain temporal domains of
the image.
Technically, watermarking is not a steganographic form. Strictly, steganography conceals data in
the image; watermarking extends the image information and becomes an attribute of the cover
image, providing license, ownership or copyright details. Masking techniques are more suitable
for use in lossy JPEG images than LSB insertion because of their relative immunity to image
operations such as compression and cropping.
10.2.3 Algorithms and transformations:
Because they are high quality color images with good compression, it is desirable to use JPEG
images across networks such as the Internet. Indeed, JPEG images are becoming abundant on the
Internet. JPEG images use the discrete cosine transform (DCT) to achieve compression. DCT is a
lossy compression transform, because the cosine values cannot be calculated precisely, and
rounding errors may be introduced. Variances between the original data and the recovered data
depends on the values and methods used the calculate the DCT.Images can also be processed
using fast Fourier transformation and wavelet transformation. Other properties such as luminance
can also be utilised. The HVS has a very low sensitivity to small changes in luminance, being
able to discern changes of no less than one part in thirty for random patterns. This figure goes up
to one part in 240 for uniform regions of an image.
Modern steganographic systems use spread-spectrum communications to transmit a narrowband
signal over a much larger bandwidth so that the spectral density of the signal in the channel looks
like noise. The two different spread-spectrum techniques these tools employ are called
directsequence and frequency hopping. The former hides information by phase-modulating the
data signal (carrier) with a pseudorandom number sequence that both the sender and the receiver
know. The latter divides the available bandwidth into multiple channels and hops between these
channels (also triggered by a pseudorandom number sequence). The Patchwork method is based
on a pseudorandom, statistical process that takes advantage of the human weaknesses to
luminance variation. Using redundant pattern encoding to repeatedly scatter hidden information
throughout the cover image, like a patchwork, Patchwork can hide a reasonably small message
many times in a image. In the Patchwork method, n pairs of image points (a,b) are randomly
chosen. The brightness of a is decreased by one and the brightness of b is increased by one. For a
labeled image, the expected value of the sum of the differences of the n pairs of points is then 2n.
15 | P a g e
Bender shows that after JPEG compression, with the quality factor set to 75, the message can
stillbe decoded with an 85 This algorithm is more robust to image processing such as cropping
and rotating, but at the cost of message size. Techniques such as Patchwork are ideal for
watermarking of images. Even if the image is cropped, there is a good probability that the
watermark will still be readable.
Other techniques encrypt and scatter the hidden throughout the image in some predetermined
manner. It is assumed that even if the message bits are extracted, they will be useless without the
algorithm and stego-key to decode them. Although such techniques do help protect against
hidden message extraction, they are not immune to destruction of the hidden message through
image manipulation.
11. SYSTEM DESIGN:
These are the steps followed in image hiding while transmission and de noising after receiving:
1. Get a cover image (publicly accessible material)
2. Take the information to be hidden (message or image)
3. Combine cover image with the information to be hidden(we follow LSB algorithm for this)
4. While transmission it will be corrupted by noise
5. Use any of the filtering methods, ex: wiener filtering for de noising in wavelet domain
6. Here filter is employed in order to remove the noise
7. During extraction a password check is provided
8. If password is matched then extraction of hidden information
12. CONCLUSION:
In this paper, we take an introductory look at steganography. Several methods for hiding data in,
images were described, with appropriate introductions to the environments of each medium, as
well as the strengths and weaknesses of each method.The key algorithm for designing the
steganography system has been dealt. Most data-hiding systems take advantage of human
perceptual weaknesses, but have weaknesses of their own. We conclude that for now, it seems
that no system of data-hiding is totally immune to attack.
However, steganography has its place in security. Though it cannot replace cryptography totally,
it is intended to supplement it. Its application in watermarking and fingerprinting, for use in
detection of unauthorised, illegally copied material, is continually being realised and developed.
Also, in places where standard cryptography and encryption is outlawed, steganography can be
used for covert data transmission. Steganography can be used along with cryptography to make
an highly secure data high way.Formerly just an interest of the military, Steganography is now
gaining popularity among the masses. Soon, any computer user will be able to put his own
watermark on his artistic creations.
13. BIBLIOGRAPHY:
16 | P a g e
1.M.Kuhn.
Steganography mailing list.
WWW: http://www.jjtc.com/Steganography/steglist.htm, 1995.
Private Site, Hamburg, Germany
2. N.F. Johnson.
Steganography.
WWW: http://www.jjtc.com/stegdoc/.
George Mason University
3. C. Kurak and J. McHugh.
4. W. Bender, D. Gruhl, N. Morimoto, and A. Lu.
Techniques for data hiding.
In IBM Systems Journal, Vol. 35, Nos. 3-4, pages 313-336, February 1996.