Encoding Secret Messages In Text Information Technology Essay

World has become a global village we can easily send receive, view information all over the world easily I addition to all the advantages of this world there are certain problems like the information send on the network is not safe and secure and third party can easily view this information. In this paper a technique is presented in which data is hidden in the colored image by analyzing the noise of image.

The rapid expansion of the Internet in the past years has increased the availability of digital data such as audio, images and videos to the public. As we have witnessed in the past few months, the problem of protecting multimedia information becomes more and more important and a lot of copyright owners are concerned about protecting any illegal duplication of their data or work. Some serious work needs to be done in order to maintain the availability of multimedia information but, in the meantime, the industry must come up with ways to protect intellectual property of creators, distributors or simple owners of such data. This is an interesting challenge and this is probably why so much attention has been drawn toward the development of digital images protection schemes. Of the many approaches possible to protect visual data, digital steganography/ watermarking is probably the one that has received most interest.

Steganography, which allows the secret embedding of information in a host data, has now come as a widely accepted approach for secure occupation and transfer of data over the network. A lot of effort has, therefore, been dedicated to the development of robust steganographic schemes to achieve these goals. Moreover, the same scheme can be used for efficient secure information transfer in form of audio, image, text or video.

Steganography is defined by Markus Kahn as follows, “Steganography is the art and science of communicating in a way which hides the existence of the communication. Steganography is often combined with cryptography so that even if the message is discovered it cannot be read. The key difference between Cryptography and Steganography lies with the fact that when a message is encrypted, one already knows that the message exists and it is encrypted, whereas with Steganography you might not even know (or observe) that there does exists a message too, simply because its hidden behind an image, video or an audio etc… which without keen observation might go without any suspicion.

Steganographic research is primarily driven by the lack of strength in the cryptographic systems on their own and the desire to have complete secrecy in an open-systems environment. Many governments have created laws that either limit the strength of cryptosystems or prohibit them completely. This has been done primarily for fear by law enforcement not to be able to gain intelligence by wiretaps, etc. This unfortunately leaves the majority of the Internet community either with relatively weak and a lot of the times breakable encryption algorithms or none at all. Civil liberties advocates fight this with the argument that “these limitations are an assault on privacy”. This is where Steganography comes in. Steganography can be used to hide important data inside another file so that only the parties intended to get the message even knows a secret message exists.

Coding secret messages in digital images is by far the most widely used of all methods in the digital world of today. This is because it can take advantage of the limited power of the human visual system (HVS). Almost any plain text, cipher text, image and any other media that can be encoded into a bit stream can be hidden in a digital image. With the continued growth of strong graphics power in computers and the research being put into image based Steganography, this field will continue to grow at a very rapid pace.

In this project, a novel technique is introduced for secure information transfer and content authentication of digital content. This project report is divided into ten chapters. Chapter 1, the current chapter covers the introduction to the project, importance of the Project and the layout of this Project Report. Chapter 2 gives the brief history of steganography, modern steganography and techniques. Chapter 3 covers the literature review.

Project Description

System:

The elements of this system are:

Message

Gray Scale Image

Using an algorithm to select pixel values of image to be replaced

Key

Output Image

Project objectives:

This system will hide a secret message or a copyright mark in an image in such a way that input data will be replaced by respective pixel values in an image and then the image of all the updated values will be created.

User will enter data (to hide it in image).

The data will be converted to binary code using asci code.

Then a colored image will be taken

Region will be selected in image for data insertion.

Binary code of image will be taken.

Pixels for data insertion will be selected by using pseudorandom generator.

Each digit of data binary code will be replaced by selected pixel lsb.

As a result the message will be embedded in the image and it can easily be extracted at the other end.

Problem statement:

It is fairly easy to hide and then unhide a secret message in a graphic, audio or video file without obviously altering the visible appearance of that file. We can hide data in various kinds of image- and audio-files. The color- respectively sample-frequencies are not changed thus making the embedding resistant against first-order statistical tests. This system will hide a secret message or a copyright mark in an image in such a way that input data will be replaced by respective pixel values in an image and then the image of all the updated values will be created. [4]

Project scope:

This approach can be used for sending secret information or a message. This can also be used to insert watermarks in an image for copyright protection. This will be highly secure and no one will suspect the message as it will be transmitted in the form of image.

Background knowledge

Steganography:

Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. The word steganography is of Greek origin and means “concealed writing” from the Greek words steganos meaning “covered or protected”, and graphein meaning “to write”. The first recorded use of the term was in 1499 by Johannes Trithemius in his Steganographia, a treatise on cryptography and steganography disguised as a book on magic. Generally, messages will appear to be something else: images, articles, shopping lists, or some other covertext and, classically, the hidden message may be in invisible ink between the visible lines of a private letter.

The advantage of steganography, over cryptography alone, is that messages do not attract attention to themselves. Plainly visible encrypted messages no matter how unbreakable will arouse suspicion, and may in themselves be incriminating in countries where encryption is illegal. Therefore, whereas cryptography protects the contents of a message, steganography can be said to protect both messages and communicating parties.

Steganography includes the concealment of information within computer files. In digital steganography, electronic communications may include steganographic coding inside of a transport layer, such as a document file, image file, program or protocol. Media files are ideal for steganographic transmission because of their large size. As a simple example, a sender might start with an innocuous image file and adjust the color of every 100th pixel to correspond to a letter in the alphabet, a change so subtle that someone not specifically looking for it is unlikely to notice it.

Steganography hides the covert message but not the fact that two parties are communicating with each other. The steganography process generally involves placing a hidden message in some transport medium, called the carrier. The secret message is embedded in the carrier to form the steganography medium. The use of a steganography key may be employed for encryption of the hidden message and/or for randomization in the steganography scheme. In summary:

steganography_medium = hidden_message + carrier + steganography_key

As an increasing amount of data is stored on computers and transmitted over networks, it is not surprising that steganography has entered the digital age. On computers and networks, steganography applications allow for someone to hide any type of binary file in any other binary file, although image and audio files are today’s most common carriers. [2]

A Brief History of Steganography

The earliest recordings of Steganography were by the Greek historian Herodotus in his chronicles known as “Histories” and date back to around 440 BC. Herodotus recorded two stories of Steganographic techniques during this time in Greece. The first stated that King Darius of Susa shaved the head of one of his prisoners and wrote a secret message on his scalp. When the prisoner’s hair grew back, he was sent to the Kings son in law Aristogoras in Miletus undetected. The second story also came from Herodotus, which claims that a soldier named Demeratus needed to send a message to Sparta that Xerxes intended to invade Greece. Back then, the writing medium was text written on wax-covered tablets. Demeratus removed the wax from the tablet, wrote the secret message on the underlying wood, recovered the tablet with wax to make it appear as a blank tablet and finally sent the document without being detected. Romans used invisible inks, which were based on natural substances such as fruit juices and milk. This was accomplished by heating the hidden text, thus revealing its contents. Invisible inks have become much more advanced and are still in limited use today.

During the times of WWI and WWII, significant advances in Steganography took place. Concepts such as null ciphers (taking the 3rd letter from each word in a harmless message to create a hidden message, etc), image substitution and microdot (taking data such as pictures and reducing it to the size of a large period on a piece of paper) were introduced and embraced as great steganographic techniques.

In the digital world of today, namely 1992 to present, Steganography is being used all over the world on computer systems. Many tools and technologies have been created that take advantage of old steganographic techniques such as null ciphers, coding in images, audio, video and microdot. With the research this topic is now getting we will see a lot of great applications for Steganography in the near future. [1]

Modern steganography:

Modern steganography refers to hiding information in digital images, audio files or even video. There are many methods and tools to do that. Nevertheless, and to have double protection, secret messages are first encrypted and then hidden using a steganography tool. [4]

The following formula provides a very generic description of the pieces of the steganographic process:

cover_medium + hidden_data + stego_key = stego_medium

In this context, the cover_medium is the file in which we will hide the hidden_data, which may also be encrypted using the stego_key. The resultant file is the stego_medium (which will, of course. be the same type of file as the cover_medium). The cover_medium (and, thus, the stego_medium) are typically image or audio files. In this article, I will focus on image files and will, therefore, refer to the cover_image and stego_image. [6]

Steganographic Types:

Encoding Secret Messages in Text

Encoding secret messages in text can be a very challenging task. This is because text files have a very small amount of redundant data to replace with a secret message. Another drawback is the ease of which text based Steganography can be altered by unwanted parties by just changing the text itself or reformatting the text to some other form (from .TXT to .PDF, etc.). There are numerous methods by which to accomplish text based Steganography.

Line-shift encoding involves actually shifting each line of text vertically up or down by as little as 3 centimeters. Depending on whether the line was up or down from the stationary line would equate to a value that would or could be encoded into a secret message. Word-shift encoding works in much the same way that line-shift encoding works, only we use the horizontal spaces between words to equate a value for the hidden message. This method of encoding is less visible than line-shift encoding but requires that the text format support variable spacing.

Feature specific encoding involves encoding secret messages into formatted text by changing certain text attributes such as vertical/horizontal length of letters such as b, d, T, etc. This is by far the hardest text encoding method to intercept as each type of formatted text has a large amount of features that can be used for encoding the secret message.

All three of these text based encoding methods require either the original file or the knowledge of the original files formatting to be able to decode the secret message. [1]

Digital watermarking (digital watermarking):

Whenever there is a topic about steganography now a day, Digital Watermarking is also mentioned. It refers to embedding hidden messages as well, but not for the purpose of sending secret information. Instead, Watermarking is usually used for the following:

Copyright protection: include ownership information.

Copy protection: include instructions to stop data copying devices from making and distributing copies of the original.

Prove data authenticity.

Tracking: If copies of a file are distributed illegally, the source can be revealed if the master copies had unique watermarks included. [4]

Hiding messages in audio files

Two known methods to store message in audio files are: Frequency Domain and Time Domain.

In Frequency Domain, a message can be stored in practically unused frequencies of audio files. For instance, In a CD where the sample rate is 44.1 kHz, the highest frequency without aliasing is 22.05 kHz. Now, because the average peak frequency that an adult can hear is approximately 18 kHz, this leaves 4 kHz of frequency that is “practically unused”. This space can then be used to hide a message (a copyright message for example).

In Time Domain, a message can be stored in the LSBs, something similar to what we saw with images. To maintain CD quality, it is important to encode at 16 bits per sample at a rate of 44.1kHz. However, we can also record at 8 bits per sample using the high significant bits (first bits on your left-hand side) and save the other 4 LSBs to hide our message without making any perceptible change to the audio quality. In a comparison between the two, detecting messages hidden with time domain is harder because it requires more resources. [4]

Digital Carrier Methods

There are many ways in which messages can be hidden in digital media. Digital forensics examiners are familiar with data that remains in file slack or unallocated space as the remnants of previous files, and programs can be written to access slack and unallocated space directly. Small amounts of data can also be hidden in the unused portion of file headers.

Information can also be hidden on a hard drive in a secret partition. A hidden partition will not be seen under normal circumstances, although disk configuration and other tools might allow complete access to the hidden partition (Johnson et al. 2001). A hidden file system is particularly interesting because it protects the user from being inextricably tied to certain information on their hard drive. This form of plausible deniability allows a user to claim to not be in possession of certain information or to claim that certain events never occurred. Under this system users can hide the number of files on the drive, guarantee the secrecy of the files’ contents, and not disrupt nonhidden files by the removal of the steganography file driver.

Another digital carrier can be the network protocols. Covert Transmission Control Protocol by Craig Rowland, for example, forms covert communications channels using the identification field in Internet Protocol packets or the sequence number field in Transmission Control Protocol segments. By overwriting the least significant bit, the numeric value of the byte changes very little and is least likely to be detected by the human eye or ear.

Newer, more complex steganography methods continue to emerge. Spread-spectrum steganography methods are analogous to spread-spectrum radio transmissions (developed in World War II and commonly used in data communications systems today) where the “energy” of the signal is spread across a wide-frequency spectrum rather than focused on a single frequency, in an effort to make detection and jamming of the signal harder. Spread-spectrum steganography has the same function avoid detection. These methods take advantage of the fact that little distortions to image and sound files are least detectable in the high-energy portions of the carrier (i.e., high intensity in sound files or bright colors in image files). Even when viewed side by side, it is easier to fool human senses when small changes are made to loud sounds and/or bright colors. [2]

Image steganography

Images are the most popular cover objects used for steganography. In the domain of digital images many different image file formats exist, most of them for specific applications. For these different image file formats, different steganographic algorithms exist.

Image definition

To a computer, an image is a collection of numbers that constitute different light intensities in different areas of the image. This numeric representation forms a grid and the individual points are referred to as pixels. Most images on the Internet consists of a rectangular map of the image’s pixels (represented as bits) where each pixel is located and its color. These pixels are displayed horizontally row by row. The number of bits in a color scheme, called the bit depth, refers to the number of bits used for each pixel. The smallest bit depth in current color schemes is 8, meaning that there are 8 bits used to describe the color of each pixel. Monochrome and grayscale images use 8 bits for each pixel and are able to display 256 different colors or shades of grey. Digital color images are typically stored in 24-bit files and use the RGB color model, also known as true color. All color variations for the pixels of a 24-bit image are derived from three primary colors: red, green and blue, and each primary color is represented by 8 bits. Thus in one given pixel, there can be 256 different quantities of red, green and blue, adding up to more than 16-millioncombinations, resulting in more than 16-million colors. Not surprisingly the larger amount of colors that can be displayed, the larger the file size.

Image and Transform Domain

Image steganography techniques can be divided into two groups: those in the Image Domain and those in the Transform Domain. Image also known as spatial domain techniques embed messages in the intensity of the pixels directly, while for transform also known as frequency domain, images are first transformed and then the message is embedded in the image. Image domain techniques encompass bit-wise methods that apply bit insertion and noise manipulation and are sometimes characterized as “simple systems”. The image formats that are most suitable for image domain steganography are lossless and the techniques are typically dependent on the image format. Steganography in the transform domain involves the manipulation of algorithms and image transforms. These methods hide messages in more significant areas of the cover image, making it more robust. Many transform domain methods are independent of the image format and the embedded message may survive conversion between lossy and lossless compression. In the next sections steganographic algorithms will be explained in categories according to image file formats and the domain in which they are performed.

Least Significant Bit

Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover image. The least significant bit (in other words, the 8th bit) of some or all of the bytes inside an image is changed to a bit of the secret message. When using a 24-bit image, a bit of each of the red, green and blue colour components can be used, since they are each represented by a byte. In other words, one can store 3 bits in each pixel. An 800 Ã- 600 pixel image, can thus store a total amount of 1,440,000 bits or 180,000 bytes of embedded data. For example a grid for 3 pixels of a 24-bit image can be as follows:

(00101101 00011100 11011100)

(10100110 11000100 00001100)

(11010010 10101101 01100011)

When the number 200, which binary representation is 11001000, is embedded into the least significant bits of this part of the image, the resulting grid is as follows:

(00101101 00011101 11011100)

(10100110 11000101 00001100)

(11010010 10101100 01100011)

Although the number was embedded into the first 8 bytes of the grid, only the 3 underlined bits needed to be changed according to the embedded message. On average, only half of the bits in an image will need to be modified to hide a secret message using the maximum cover size. Since there are 256 possible intensities of each primary colour, changing the LSB of a pixel results in small changes in the intensity of the colours. These changes cannot be perceived by the human eye – thus the message is successfully hidden. With a well-chosen image, one can even hide the message in the least as well as second to least significant bit and still not see the difference. In the above example, consecutive bytes of the image data from the first byte to the end of the message are used to embed the information. This approach is very easy to detect. A slightly more secure system is for the sender and receiver to share a secret key that specifies only certain pixels to be changed. Should an adversary suspect that LSB steganography has been used, he has no way of knowing which pixels to target without the secret key.

In its simplest form, LSB makes use of BMP images, since they use lossless compression. Unfortunately to be able to hide a secret message inside a BMP file, one would require a very large cover image. Nowadays, BMP images of 800 Ã- 600 pixels are not often used on the Internet and might arouse suspicion. For this reason, LSB steganography has also been developed for use with other image file formats. [7]

Masking and filtering:

Masking and filtering techniques for digital image encoding such as Digital Watermarking (i.e.- integrating a companies logo on there web content) are more popular with lossy compression techniques such as (.JPEG). This technique actually extends an images data by masking the secret data over the original data as opposed to hiding information inside of the data. Some experts argue that this is definitely a form of Information Hiding, but not technically Steganography. The beauty of Masking and Filtering techniques are that they are immune to image manipulation which makes there possible uses very robust. Techniques that use complex algorithms, image transformation techniques and image encryption techniques are still relatively new, but show promise to be more secure and robust ways to use digital images in Steganography. [1]

Steganographic Protocols:

There are basically three types of steganographic protocols used. They are Pure Steganography, Secret Key Steganography and Public Key Steganography.

Pure Steganography:

Pure steganography is defined as a steganographic system that does not require the exchange of a cipher such as a stego-key. This method of Steganography is the least secure means by which to communicate secretly because the sender and receiver can rely only upon the presumption that no other parties are aware of this secret message. Using open systems such as the Internet, we know this is not the case at all.

Secret Key Steganography:

Secret steganography is defined as a steganographic system that requires the exchange of a secret key (stego-key) prior to communication. Secret Key Steganography takes a cover message and embeds the secret message inside of it by using a secret key (stego-key). Only the parties who know the secret key can reverse the process and read the secret message. Unlike Pure Steganography where a perceived invisible communication channel is present, Secret Key Steganography exchanges a stego-key, which makes it more susceptible to interception. The benefit to Secret Key Steganography is even if it is intercepted, only parties who know the secret key can extract the secret message.

Public Key Steganography:

Public steganography takes the concepts from Public Key Cryptography as explained below. Public Key Steganography is defined as a steganographic system that uses a public key and a private key to secure the communication between the parties wanting to communicate secretly. The sender will use the public key during the encoding process and only the private key, which has a direct mathematical relationship with the public key, can decipher the secret message. Public Key Steganography provides a more robust way of implementing a steganographic system because it can utilize a much more robust and researched technology in Public Key Cryptography. It also has multiple levels of security in that unwanted parties must first suspect the use of steganography and then they would have to find a way to crack the algorithm used by the public key system before they could intercept the secret message.

Literature review

TECHNIQUE 1

Main idea:

In this method secret message is inserted in LSB of cover image by analyzing the value or intensity of each pixel, more LSB’s of darker image can be replaced.

Features characteristics:

Key is XORed with all bytes of message to be embedded

Message is recovered by XOR operation by same key

Every pixel value of image is analyzed before embedding message

No of bits to be inserted depends on value of that pixel

Advantages:

It is very simple to implement

This technique performs well in all parameters as compared to (for text also)

Every pixel value of image is analyzed before embedding message

No of bits to be inserted depends on value of that pixel

Disadvantages:

Embedding capacity varies from image to image

Hacker can easily recover the message by analyzing pixel values of image

Technique:

The cover image used is a gray scale image. Before embedding the data we use 8 bit secret key and XOR with all the bytes of the message to be embedded. Message is recovered by XOR operation by the same key. Every pixel value in this image is analyzed and the following checking process is employed

If value of the pixel say gi, is in the range 240 ≤ gi ≤255 (first 4 Most Significant Bits (MSB’s). If they are all 1’s) then we embed 4 bits of secret data into the 4 LSB’s of the pixel.

If the value of gi, is in the range 224 ≤ gi ≤239 (First 3 MSB’s are all 1’s) then we embed 3 bits of secret data into the 3 LSB’s of the pixel.

If the value of gi, is in the range 192 ≤ gi ≤223 (First 2 MSB’s are all 1’s) then we embed 2 bits of secret data into the 2 LSB’s of the pixel.

For the values in the range 0 ≤gi ≤192 we embed 1 bit of secret data in to 1 LSB of the pixel.

We can retrieve the secret data from the gray values of the stego image by again checking the first four MSB’s of the pixel value and retrieve the embedded data.

Graphical model:

COVER IMAGE

240≤gi≤255

0≤gi≤192

192≤gi≤223

224≤gi≤239

1 LSB’s will be replaced

4 LSB’s will be replaced

3 LSB’s will be replaced

2 LSB’s will be replaced

Key Generation:

8 bit key

Message

XOR

Encrypted message

TECHNIQUE 2:

In this method pixel are chosen through a password this method each byte of information is hidden in two pixels.

Features:

Information is hidden in the least significant bits (LSB) of pixels colors

In this method each byte of information is hidden in two pixels

By using a password, two pixels are selected in which a byte of information is hidden

Human eyes are less sensitive to blue colors, so more significant changes may be applied to blue colors.

For decoding of information size of message or information must be known and that will be in the image

Advantages

The advantages of this method are:

The probability that one can detect a stegano image is relatively low, due to the high volume of images exchanged between mobile phones and computers.

The password is not stored in the stegano image; therefore it is difficult to detect the password.

Because the password is used, it is difficult to detect the information hidden in the image.

The decoding program uses a few kilobytes of memory.

The advantage of this method is that there is no need to search for an empty pixel in the block, because we have the empty pixel numbers of the current block in an array

The advantage of this work is that the pixels are filled in a random order and can not decode without knowing the password

Disadvantages:

The disadvantages of this method are:

There is a variety of mobile phones on the market for which there isn’t a standard operating system, so it is not possible to produce a coder program for all of them.

The stegano image is sensitive to the size and other characteristics of the image; therefore changing the image could destroy the hidden information.

Algorithm:

In this method the

Image is segmented into n blocks of m pixels.

Then using a password, a block is selected to embed information in empty pixel of block.

The algorithm for selecting a block and an empty pixel in that block is as follows:

If that block starts with k number pixel and the total number of pixel in that block are m than the last pixel of that block would be k-1+m.

An array of size m+1 is used to keep in track the number of empty pixels of that block. This array contains the number of pixels having no data.the last element of array (m+1) contains the number of empty pixels. According to the password, an empty pixel is selected and the last empty pixel number is copied to this array cell.

As we start loading our data total number of empty pixels of the block decreases by one. This method is also used for selecting a block to hide the information in itself. The figure-1 shows the array before and after selecting a pixel.

Technique 3:

Main idea:

The main idea behind this method is to change pixel values of an image (inserting a message) so that it is imperceptible to human eye. The message is inserted by evaluating the luminance intensity and contrast of the region.

Features characteristics:

For each pixel of a gray-scale image, at least 4 bits can be used for messages embedding.

Pixel value is changed after evaluating the contrast and luminance characteristics.

On the average case, this method can embed 4:025 bits in each pixel, the embedding capacity is a little more than 4 bits

The embedding capacity of an image is embedded in cover image.

The LSBs of pixel should be identical to the embedded message bits.

Goal is to reduce the embedding error, so that can more embedded in the cover-image

The IGSC component compensates the embedding error from neighboring pixels to eliminate the false contouring without impairing the quality of image perception.

Graphical model:

Advantages:

The great benefit of this method is that no false contours appear in the smooth area.

Therefore, the sender can choose different methods alternatively to increase the difficulty of steganalysis on these stego-images. This is the major benefit of supporting these two security methods in the proposed model

To achieve the highest quality, most similar gray-scale is used to replace the original one.

The embedding capacity of an image is embedded in cover mage

The local characteristics of the image almost remains same after embedding message

Technique:

The Embedding Module

The embedding module consists of three major components:

CE component

The embedding module will be applied to each pixel. Assume that the gray scale of one pixel p at coordinates (x, y) is denoted by f(x, y), the 8-neighbors of p are shown in Fig. 1. For p, f(x, y) will be modified according to its embedding capacity, which depends on its gray scale and the gray-scale variation of the upper and left neighbors (the shaded pixels in Fig. 1).

Let

Max(x, y) = max {f(x – 1; y – 1), f(x – 1, y), f(x – 1, y + 1), f(x, y – 1)}

Min(x, y) = min {f(x – 1, y -1), f(x -1, y), f(x -1, y + 1), f(x, y – 1)}

D(x, y) = Max(x, y) – Min(x, y)

Except for the boundary pixels in an image, the embedding capacity Kn(x, y) of each pixel (x, y) is defined as

Kn(x, y) = └log2 D(x, y)┘

According to the HVS, the greater a gray-scale is, the more change of the gray- scale could be tolerated. Thus, the embedding capacity should be limited by the gray scale of current pixel. Here, an upper bound for embedding capacity at pixel (x, y) is defined as

U(x; y) = 4, if f(x; y) <=t

5, otherwise.

On the other hand, according to the proposed IGSC component, the lower bound for embedding capacity could be set as 4 bits. So the embedding capacity K(x, y) of each pixel can be computed by the following expression.

K(x, y) = min {max {Kn(x, y), 4}, U(x; y)}

The MER Component

In general, 8 bits are used to represent the intensity of each pixel in a gray-scale image. If we want to embed k (k < 8) bits in a pixel, then replacing the k-LSBs of the pixel will introduce the smallest error than replacing any other k bits. In this case, the maximum embedding error introduced is 2k-1. In IGSC component, the embedding error is evenly spread to the bottom and right neighboring pixels. Let e(x; y) denote the embedding error of pixel p at coordinates (x; y), these four bottom-right neighboring gray-scales are then modified according to the following expressions.

f (x; y + 1) = f(x; y + 1)+1/4 e(x; y);

f(x + 1; y -1) = f(x + 1; y -1) +1/4e(x; y);

f(x + 1; y) = f(x + 1; y) +1/4e(x; y);

f(x + 1; y + 1) = f(x + 1; y + 1) +1/ 4e(x; y):

Using component will increase the embedding capacity and will reduce false contorting.

The Extracting Module

The extracting module in the proposed method is very simple. Using the same CE component as that in the embedding module to compute the embedded capacity of each pixel, those embedding messages can be extracted directly by applying the embedding process in reverse.

Evaluation of different techniques

All the above mentioned algorithms for image steganography have different strong and weak points and it is important to ensure that one uses the most suitable algorithm for an application. All steganographic algorithms have to comply with a few basic requirements. The most important requirement is that a steganographic algorithm has to be imperceptible. These requirements are as follows:

Invisibility

The invisibility of a steganographic algorithm is the first and foremost requirement, since the strength of steganography lies in its ability to be unnoticed by the human eye. The moment that one can see that an image has been tampered with, the algorithm is compromised

 Payload capacity

Unlike watermarking, which needs to embed only a small amount of copyright information, steganography aims at hidden communication and therefore requires sufficient embedding capacity

Robustness against statistical attacks

Statistical steganalysis is the practice of detecting hidden information through applying statistical tests on image data. Many steganographic algorithms leave a’signature’ when embedding information that can be easily detected through statistical analysis. To be able to pass by a warden without being detected, a steganographic algorithm must not leave such a mark in the image as be statistically significant.

Robustness against image manipulation

In the communication of a stego image by trusted systems, the image may undergo changes by an active warden in an attempt to remove hidden information. Image manipulation, such as cropping or rotating, can be performed on the image before it reaches its destination. Depending on the manner in which the message is embedded, these manipulations may destroy the hidden message. It is preferable for steganographic algorithms to be robust against either malicious or unintentional changes to the image.

Independent of file format

With many different image file formats used on the Internet, it might seem suspicious that only one type of file format is continuously communicated between two parties. The most powerful steganographic algorithms thus possess the ability to embed information in any type of file. This also solves the problem of not always being able to find a suitable image at the right moment, in the right format to use as a cover image.

Unsuspicious files

This requirement includes all characteristics of a steganographic algorithm that may result in images that are not used normally and may cause suspicion. Abnormal file size, for example, is one property of an image that can result in further investigation of the image by a warden. [7]

Methodology

Description of software:

Reading a gray scale image My system will be:

Output Image

selecting pixel values of image to be replaced

KEY

The goal is to produce an image that looks exactly the same to a human eye but still allows its positive identification in comparison with the owner’s key if necessary.

Applicable Standards

The platform standard shall be Windows Professional.

Input/ output format:

Input file can be any kind of image or text, but the output will be in form of image.

Hardware Requirement

Intel Core 2 Due

1 GB RAM

Software Requirement

Matlab

Micrososft Visio

Performance Requirements

The Interface of product is very easy which help to operate easily. Help is also provided so that user can get Help.

Proposed Model

Model:

Entropy

Image

Region selected for message insertion

Secret Message

Selecting Pixels By pseudorandom generator

Encryption

B

Encrypted Text

Bit value of image pixels

A

Data Insertion

ASCII code of text

E=DRDM of pixels after replacing pixel bit with message bits

F=DRDM after adjusting value of neighboring bits

B

Bits of text

E<F

E>F

New pixel value = F

New pixel value = E

Flow Chart

If E<F the pixel value will be of E else F

E=DRDM of pixels after replacing pixel bit with message bits

F=DRDM after adjusting value of neighboring bits

Ascii Code

Encryption

Bits

IGSC component

Data Insertion

Image

Selecting a region in image by entropy

Secret Message

Selecting pixels by pseudorandom number generator

Implementation

[1] SANS Institute InfoSec Reading Room A detailed look at Steganographic Techniques and their use in an Open-Systems Environment By: Bret Dunbar 01/18/2002

[2] An Overview of Steganography for the Computer Forensics Examiner Gary C. Kessler Associate Professor Computer and Digital Forensics Program Champlain College Burlington, Vermont

[3] Digital image steganography of encrypted text In the fall of 2003, the Ubiquitous Software Engineers (U-S-E) created a steganography program under the direction of Professor Doug Tygar for the class “Software Engineering.”

[4] Introduction to Modern Steganography January 11th, 2010 | Author: Haider al-Khateeb

[5] Steganalysis of Images Created Using Current Steganography Software Neil F. Johnson and Sushil Jajodia Center for Secure Information Systems George Mason University Fairfax, Virginia.

[6]Steganography: Hiding Data Within Data Gary C. Kessler

September 2001 An edited version of this paper with the title “Hiding Data in Data” originally appeared in the April 2002 issue of Windows & .NET Magazine .

[7] An overview of image steganography by T. Morkel 1, j.h.p. Eloff 2, m.s. Olivier 3

Information and computer security architecture (icsa) research group Department of computer science University of pretoria, 0002, pretoria, south africa