Final Project Report

IMAGE BASED STEGANOGRAPHY USING LSB INSERTION TECHNIQUE

A Project report

Submitted in partial fulfillment of the requirement

For the award of the degree of

BACHELOR OF TECHNOLOGY

IN

ELECTRONICS AND COMMUNICATION ENGINEERINGBy

K. Sai Pranitha (07FE1A0419)

T. Usha Sri (07FE1A0423)

M. V. R. Amaralingeswara Rao (08FE5A0417)

V. Kanaka Rao (08FE5A0418)

Under the guidance of

Mr. M. Suman Assistant Professor

Department of Electronics and Communication Engineering

VIGNAN’S LARA INSTITUTE OF TECHNOLOGY AND SCIENCE

VADLAMUDI – 522 213

GUNTUR (Dt.)

(2010-11)

CERTIFICATE

This is to certify that this project report entitled

IMAGE BASED STEGANOGRAPHY USING LSB INSERTION TECHNIQUE

is a bonafide record of work done by



M. V. R. Amaralingeswara Rao (08FE5A0417)


Under my guidance and supervision and submitted in partial fulfillment of the requirements for the award of the degree of Bachelor of Technology in Electronics and Communication Engineering by the Jawaharlal Nehru Technological University, Kakinada.

M. SUMAN Assistant Professor

M. V. H. BHASKARA MURTHY Professor and HOD

Department of Electronics and Communication Engineering

VIGNAN’S LARA INSTITUTE OF TECHNOLOGY AND SCIENCE

VADLAMUDI – 522 213

GUNTUR (Dt.)

(2010-11)

ACKNOWLEDGEMENT

We would like to take this opportunity to express our profound sense of gratitude to our

guide Mr. M. SUMAN, Assistant Professor, Vignan’s Lara Institute of Technology and Science,

for his constant guidance, supervision, motivation and encouragement all the way during the

project, his annotations and criticisms are the key behind successful completion of this project

work.

We also like to thank our beloved Head of the Department, Electronics and

Communication Engineering, Prof. M. V. H. BHASKARA MURTHY garu, for his cooperation and

encouragement in completing this project by providing us proper lab facilities.

We, the members of the project, express thanks to the people who were directly or

indirectly involved in this project for their overwhelming cooperation. Finally we would like to

extend our heartfelt thanks to our beloved parents whose blessings and encouragement were

always there as a source of strength and inspiration.

Project Associates



M.V. R. Amaralingeswara Rao (08FE5A0417)


CONTENTS

Abstract i

List of Figures ii

1. INTRODUCTION 1

2. STEGANOGRAPHY TECHNIQUES 2

2.1 Kerk off Principle 2

3. STEGANOGRAPHY METHODS 3

3.1 Substitution Method 3

3.2 Proposed Method 43.3 Visual Perception 43.4 Difference Analysis 53.5 Distortion Analysis 5

3.6 Depth Vs Distortion Analysis 53.7 Steganography in Images 6

4. STEGANOGRAPHY DIAGRAMATIC FLOW 7

4.1 Images 74.2 Image Compression 8

5. IMAGE ENCODING TECHNIQUE 9

5.1 Least Significant Bit Insertion 95.2 Advantages of LSB 105.3 Masking and Filtering 105.4 Algorithms and Transformations 11

6. SYSTEM DESIGN 13

7. SECURITY 14

8. FUTURE SCOPE 15

9. CONCLUSION 16

10. REFERENCES 17

I

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 software 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.

Image Based Steganography Using LSB Insertion Technique 2010-2011

II

LIST OF FIGURES

1. Frame work of Steganography Based Information Protection Method 42. Scheme of Steganography 5

3. Depth Vs Distortion Analysis 64. Steganography Diagrammatic Flow 7


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1. INTRODUCTION

Now a days, various modes of communication like LAN, WAN and INTERNET are widely used for communicating information from one place to another around the globe. Such communication networks are open which any one can access easily. They are regularly monitored and an intercepted.

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. A message is embedded in a cover media in an invisible manner so that one could not suspect about its existence.

In this paper we present a substitution based information protection method where we combine cryptographic, steganographic and signal processing concepts together for achieving security. The method is known as Steganography Based Information Protection method. In this method we substitute the information bit in randomly selected pixels at random places within LSB region.


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2. STEGANOGRAPHY TECHNIQUE

Steganography is the art and science of communicating in a way which hides the existence of the secret message communication. It aims to hide information /covered writing. Information to be protected is hidden in another data known as cover or carrier. Data containing hidden message are called as Steganos or Stegos. Steganos look like cover data and it is difficult to differentiate between them. Steganography based communication over easily accessible platforms to prevent leakage of information.

2.1 Kerck Off 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.


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3. STEGANOGRAPHY METHODS

According to modification in covers, the methods can be categorized as

i. Substitutionii. Transform domain

iii. Spread spectrumiv. Statisticalv. Distortion

vi. Cover generation

3.1 Substitution Method

It is commonly used simple method in which we can put information bits in LSB sequentially at fixed place, randomly at fixed place or randomly at random places in cover pixels. The message to be protected passes through scanning, coding, encryption process to form an embedded message.

Scanning, coding, encryption steps make the information unintelligible so that one cannot extract plain message.

Embedding make the message invisible so that one cannot detect it. Reshaping spreads the message so that embedded message can be detected from distorted steganos by authorized receivers.

Cover processing makes detection of embedded message more difficult since the distortion is either due to noise addition or due to message embedding. This would increases the robustness and security. Many attacks on such steganographic systems are suggested. Some attacks that can be applied are given below:

a. Stego-Only Attackb. Message-Stego Attackc. Cover-Stego Attackd. Message-Cover-Stego Attack


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3.2 Proposed Method

The framework of proposed Steganography Based Information Protection method is shown in Fig 1. Its description is presented in the following steps.

FRAME WORK OF SBIPM

Fig 1: Frame Work of Steganography Based Information Protection Method

3.3 Visual Perception

For any steganography based secure system, the perception of steganos should be as cover image itself so that one cannot differentiate them and detect the existence of embedded message.


Encryption Key. Other Keys

Stego Work

Cover Work

Information to Hide

Embedding Algorithm

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Fig 2: Scheme of Steganography

3.4 Difference Analysis

The "difference-images” obtained by taking the difference between cover or processed cover and stego image are invisible. For making the difference visible in "difference-images”, for visual interpretation, we first increase differences by multiplication of weight factor and then revert the values to get strengthened "difference-images". From analysis of these "difference-images ", on could not say that the changes are either due to cover processing or message embedding and hence we can say that the method is safe from known cover-stego attack.

3.5 Distortion Analysis

Distortion analysis of stego images is carried out by studying distortion / similarity messages statistically. There are many methods for measuring distortion that can be used for distortion analysis. Distortion between two different images is measured by considering Mean Square Error (MSE), Mean Absolute Error (MAE) or Histogram Similarity (HS).

3.6 Depth Vs Distortion Analysis

Distortion occurred in different steganos is required by varying the depth of hiding for embedding information in cover image. The relation between depth of hiding used and distortion occurred in the stego images is shown in Fig. that depth of hiding within some LSB region is most suitable for message embedding as the distortion is very small in this region. As the depth of hiding increases beyond preferable region, the distortion becomes noticeable and unsuitable for message hiding.


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Fig 3: Depth Vs Distortion Analysis

3.7 Steganography in Images

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.

When embedding data, it is important to remember the following restrictions and features:

The 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.)

The embedded data should be directly encoded into the media, rather than into a header or wrapper, to maintain data consistency across formats.

The embedded data should be as immune as possible to modifications from intelligent attacks or anticipated manipulations such as filtering and resampling. Some distortion or degradation of the embedded data can be expected when the cover data is modified. To minimize this, error correcting codes should be used. The embedded data should be self-clocking or arbitrarily re-entrant. This ensures that the embedded data can still be extracted when only a portion of the cover data is available. For example, if only a part of image is available, the embedded data should still be recoverable.

4. STEGANOGRAPHY DIAGRAMAT1C FLOW


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Fig 4: Steganography Diagrammatic Flow

4.1 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 fades. 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.


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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.

4.2 Image Compression

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" Tossy" 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 favoured 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 GIF (Graphics Interchange Format) and Microsoft's BMP (Bitmap) format.

5. IMAGE ENCODING TECHNIQUES


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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 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:

Least significant bit (LSB) insertion Masking and filtering techniques Algorithms and transformations

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.

5.1 Least 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


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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.

5.2 Advantages of LSB Insertion

Major advantage of the LSB algorithm is it is quick and easy. There has also been steganography software developed which work around LSB color alterations via palette manipulation.

LSB insertion also works well with gray-scale images. 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.

5.3 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.

5.4 Algorithms and Transformations


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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 depend on the values and methods used to calculate the DCT.

Images can also be processed using fast Fourier transformation and wavelet transformation. Other properties such as luminance can also be utilized. 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 direct-sequence 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. Bender shows that after JPEG compression, with the quality factor set to 75, the message can still be 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 pre-determined manner. It is assumed that even if the message bits are extracted, they will be


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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.


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6. SYSTEM DESIGN

These are the steps followed in image hiding while transmission and de-noising after receiving:

1. Step1: Get a cover image (publicly accessible material)2. Step2: Take the information to be hidden (message or image)3. Step3: Combine cover image with the information to be hidden(we follow LSB

algorithm)4. Step4: While transmission it will be corrupted by noise5. Step5: Use any of the filtering methods, ex: wiener filtering for de noising in wavelet

domain6. Step6: Here filter is employed in order to remove the noise7. Step7: During extraction a password check is provided8. Step8: If password is matched then extraction of hidden information.


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7. SECURITY

A method, SBIPM, for providing the security of our important information is based on the techniques of signal processing, cryptography, and steganography. The security of information has been strengthened by applying scanning, coding, and encryption, cover processing and embedding techniques in the method. Reshaping step of the method provides robustness for detecting message correctly in such situation when stego image is distorted. The method developed is safe from various attacks. Simulation and steganalysis results shown in this paper infer that one will not be able to distinguish between cover and stego images.

Thus we conclude that the strength of security achieved is very high and unauthorized receiver will not be able to get back the original message using even after exhaustive methods without the knowledge of key parameters.

Digital Steganography is interesting field and growing rapidly for information hiding in the area of information security. It plays a vital role in defense as well as civil applications. In future we will more of secure systems based on this technology. 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 unauthorized, illegally copied material, is continually being realized and developed.


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8. FUTURE SCOPE

In this report many relevant issues were presented, from a technical point of view. However, little has been done to motivate these studies. A more detailed investigation of applications, and a comparison with current techniques in steganography would have been interesting. For example, a thorough evaluation of the advantages natural language-based techniques can offer over image-based techniques could have offered valuable insights.

An important contribution of this project to natural language steganography is the linguistic sophistication of the model for word-substitution put forward. The lexical models employed in current substitution-based systems were often criticized and their inadequate behavior usually described with respect to language theory. These phenomena could have been demonstrated by example, showing texts and inadequate replacements carried out by current stego-systems. A more detailed analysis of how common these critical situations really are in typical text could have given clues for the construction of such systems, to decide whether the additional complexity introduced by statistical word-sense disambiguation is worth the effort.

Other linguistic models have been studied, in addition to the lexical ones, and put in relation to each other, and to their use for steganographic purposes. The steganographic aspects were then covered by information-theoretic models. However, little has been done to justify this choice. It might have been fruitful to present other characterizations of steganography and to compare their suitability to natural language steganography.

A central part of the problem motivating this report was that there are no models formalizing the design and analysis of natural language stegosystems. Although the present report somewhat improves the situation, by providing a systematic investigation of the topic, there is still no system to build upon for making formal claims about security or robustness in the natural language scenario.


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9. CONCLUSION

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 unauthorized, illegally copied material, is continually being realized 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 a 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.

Thus we conclude that the strength of security achieved is very high and unauthorized receiver will not be able to get back the original message using exhaustive without the knowledge of key parameters.

Digital Steganography is interesting field and growing rapidly for information hiding in the area of information security. It plays a vital role in defense as well as civil applications.


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10. REFERENCES

[1] B.Schneier, “Terrorists and Steganography”, 24 Sep. 2001, http://www.zdnet.com/zdnn/stories/comment/0,5859,2814256,00.html

[2] Y. Linde, A. Buzo, and R. M. Gray, “An Algorithm for Vector Quantizer Design,” IEEE Transactions on Communications, pp. 84-95, January 1989

[3] Andersen, R.J., Petitcolas, F.A.P., On the limits of steganography. IEEE Journal of Selected Areas in Communications, Special Issue on Copyright and Privacy Protection 16 No.4 (1998)

[4] Johnson, Neil F. and Jajodia, Sushil. “Steganography: Seeing the Unseen.” IEEE Computer February 1998, pp.2634.

[5] William Stallings; Cryptography and Network Security: Principals and Practice, Prentice Hall international, Inc.; 2002.

[6] Eric Cole ,"Hiding in Plain Sight: Steganography and the Art of Covert Communication"

[7] Gregory Kipper,"Investigator's Guide to Steganography "

[8] Stefan Katzenbeisser and Fabien, A.P. Petitcolas ," Information Hiding Techniques for Steganography and Digital Watermarking "

[9] Hiding secrets in computer files: steganography is the new invisible ink, as codes stow away on images-An article from: The Futurist by Patrick Tucker

[10] Ismail Avcıbas¸, Member, IEEE, Nasir Memon,Member, IEEE, and Bülent Sankur, Member, "Steganalysis Using Image Quality Metrics," IEEE Transactions on Image Processing, Vol 12, No.2, February 2003

[11] Niels Provos and Peter Honeyman, University of Michigan, "Hide and Seek: An Introduction to Steganography" IEEE Computer Society IEEE Security &Privacy.

[12] R. Chandramouli and Nasir Memon, "Analysis of LSB Based Image Steganography Techniques", IEEE 2001.


http://www.zdnet.com/zdnn/stories/comment/0,5859,2814256,00.html

Final Project Report

Documents

steganography methods3

frame work of steganography

steganography diagramatic

project work

security of information

project associates

image compression

amaralingeswara rao