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An Introduction of Image Steganographic Techniques

and Comparison

Ravi kumar 1, Kavita Choudhary 2, Nishant Dubey 3

1 2 3

School of computers and electronics

1, Affiliation name 2 Affiliation name 1 Email- avi15nov@yahoo.co.in 2Email- kavitalogar@yahoo.com

3

Email: nishantdubey@sify.com

Abstract- as a society, humans have continually sought new and efficient ways to communicate. The earliest methods included cave drawings, smoke signals, and drums. Advancements of civilization introduced written language, telegraph, radio/television, and most recently electronic mail. As more and more communication is conducted electronically, new needs, issues, and opportunities are born. Steganography can be used to hide or cover the existence of communication. Steganography is not a new science. Some of the first documented examples of steganography can be found in the Histories of Herodotus, where the father of history relates several stories from the times of ancient Greece. This paper intends to give an overview of image Steganography, its uses and techniques. It also attempts to identify the requirements of a good steganographic algorithm and briefly reflects on which steganographic techniques are more suitable for which applications.

Keywords: Stegno, Hide, Medium, Cryptography, Bit, Hidden, Method.

I. INTRODUCTION

At times when we communicate, we prefer that only the intended recipient have the ability to decipher the contents of the communication. We want to keep the message secret. A common solution to this problem is the use of encryption. While encryption masks the meaning of a communication, instances exist where we would prefer that the entire communication process not to be evident to any observer that is, even the fact that communication taking place is a secret. In this case, we want to keep the communication hidden. Steganography differs from cryptography in the sense that where cryptography focuses on keeping the contents of a message secret, Steganography focuses on keeping the existence of a message secret. Steganography and cryptography are both ways to protect information from unwanted parties but neither technology alone is perfect and can be compromised. Once the presence of hidden information is revealed or even suspected, the purpose of Steganography is partly defeated. The strength of steganography can thus be amplified by combining it with cryptography.

Research in steganography has mainly been driven by a lack of strength in cryptographic systems. Many governments have created laws to either limit the strength of a cryptographic system or to prohibit it altogether, forcing people to study other methods of secure information transfer. Businesses have also started to realize the potential of Steganography in communicating trade secrets or new product information. Avoiding communication through well-known channels greatly reduces the risk of information being leaked in transit. Hiding information in a photograph of the company picnic is less suspicious than communicating an encrypted file. This paper intends to offer a state of the art overview of the different algorithms used for image Steganography to illustrate the security potential of Steganography for business and personal use. After the overview it briefly reflects on the suitability of various image Steganography techniques for various applications. This reflection is based on a set of criteria that we have identified for image Steganography.

As more of today’s communications occur electronically, there have been advancements utilizing digital multimedia signals as carrier for steganographic communication. These signals are typically audio or video such as images or sounds.

“Steganography is the art of concealing the existence of information within seemingly innocuous digital images” The following formula provides a very generic description of the pieces of the steganographic process:

cover_medium + hidden_data + stego_key = stego_medium.

The cover_medium is the file in which we will hide the hidden_data, which may also be encrypted using the

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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, I will focus on image files and will, therefore, refer to the cover_image and stego_image.

Digital image is the most common type of carrier used for steganography. A digital image is composed of finite number of elements each of which has a particular location and value (gray scale). The processing of these digital images by means of a digital Computer is referred as digital image processing.

Overview of Steganography

Almost all digital file formats can be used for Steganography, but the formats that are more suitable are those with a high degree of redundancy. Redundancy can be defined as the bits of an object that provide accuracy far greater than necessary for the object’s use and display. The redundant bits of an object are those bits that can be altered without the alteration being detected easily. Image and audio files especially comply with this requirement, while research has also uncovered other file formats that can be used for information hiding. Figure 1 shows the four main categories of file formats that can be used for Steganography.

Image Steganography

As stated earlier, 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 Steganography algorithms exist.

Steganography algorithms will be explained in categories according to image file formats and the domain in which they are performed.

One Bit Stego

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Data Hiding Capacity of Image:

Total no. pixels * bits / pixel used for hiding data * 1 byte / 8 bits Two Bits Stego

Using this method two LSBs of one of the colours in the RGB value of the pixels will be used to store message bits in the image. This will involve using a palette with a maximum of 68 colours allowing for the production of a possible 196 new colours, i.e. two new colours for each existing colour. The advantage of this method is that twice as much information can be stored here than in the previous method.

Three Bits Stego

Using this method three LSBs of one of the colours in the RGB value of the pixels will be used to store message bits. This will involve using a palette with a maximum of only 32 colours allowing for the production of a possible 224 new colours, three new colours for every existing colour in the image. The data hiding capacity is three times the storage capacity of One Bit change method but the image will be even more distorted than if a 128-colour palette was used.

Four Bits Stego

Using this method four LSBs of one of the colours in the RGB value of the pixels will be used to store message bits. This will involve using a palette with a maximum of only 16 colours allowing for the production of a possible 240 new colours. This is the smallest palette that could be used for an image using Jasc Paint Shop Pro. The colours are now very restricted but an area of one particular colour in the image may have 16 variations distributed through it which could result in a certain amount of texture mitigating the effects of such a restricted palette.

Colour Cycle Stego

In order to make the detection of the hidden data more difficult it was decided to cycle through the colors values in each of the pixels in which to store the data. This also means that the same colors were not constantly being changed. For example the first data bit could be stored in the LSB of the blue value of the pixel, the second data bit in the red value and the third data bit in the green value, the alpha value will be skipped and the next colors used will be blue again. This is because changing the alpha value, which is generally 255, would look too suspicious unless the image used contained different transparency levels.

PRNG Stego

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this. Hide and Seek arranges it so that the message bits will not be beside one another but instead randomly dispersed throughout the image.

II. ALGORITHMS HIDE & SEEK (MARONEY):

A stego program that hides any data in to Graphics Interchange Format (GIF) images. It flips the LSB of pseudo randomly chosen pixels. The Hide and Seek software currently available contains two programs, which help the user in hiding information in GIF files: grey.exe converts colour GIFs into greyscale GIFs. The reduce.exe reduces the 256 colour palette to 128 colours and then duplicates the 128 colours. This is done so that entries beside each other in the colour palette are either duplicates of each other or are extremely similar to one another, so similar that they are not generally visible to the naked eye. When this has been carried out hiding information in the least significant bit won't affect the final appearance of the image.

EzStego (Machado, 1996)

One of the most popular message hiding schemes for palette-based images (GIF files) has been proposed by Machado [1]. In her method called EZ Stego, the palette is first sorted by luminance. In the reordered palette, neighboring palette entries are typically near to each other in the color space, as well. EZ Stego embeds the message in a binary form into the LSB of indices (pixels) pointing to the palette colors.

Here are the steps:

STEP 1: Find the index of the pixel's RGB color in the sorted palette.

STEP 2: Get one bit from the binary message and replace the LSB of the index. STEP 3: Find the new RGB color that the index now points to in the sorted palette. STEP 4: Find the index of the new RGB color in the original palette.

STEP 5: Change the pixel to the index of the new RGB color.

Message recovery is simply achieved by collecting the LSBs of all indices in the image file. Of course, the method could be improved by injecting message bits into randomly selected pixels based on a pseudo-random number generator (PRNG) seeded with a secret key. The algorithm is based on the premise that close colors in the luminance-ordered palette are close in the color space. However, since luminance is a linear combination of three colors R, G, and B, occasionally colors with similar luminance values may be relatively far from each other. To avoid this problem, we propose to hide message bits into the parity bit of close colors. For the color of each pixel, into which we embed message bits, we search the closest colors in the palette till we find a palette entry with the desired parity bit (parity bit of the color R, G, B is R+G+B mod 2). Since the parity bits of palette entries corresponding to real images are more or less randomly distributed, this will guarantee that we will never have to depart from the original color too much. This way, we avoid the problem of occasionally making large changes in color, which will certainly contribute to the undetectability of the message.

Fridrichs Method (Fridrich, 1999)

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The method works as follows:

STEP 1: The message is converted into a binary stream of length M.

STEP 2: The pixels into which the message is to be stored are randomly chosen using a pseudo random number generator which is seeded with a secret key.

STEP 3: A user-defined seed is used to randomly select M pixels in the image.

STEP 4: For each pixel P a set of the closest colors in the palette is calculated by measuring the distance between them. The distance between colors (R1, G1, B1) and (R2, G2, B2) is determined by:

Square root of (R1 - R2)2 + (G1 - G2)2 + (B1 - B2)2

STEP 5: If the closest color is the color of the pixel itself, the next closest color is selected until a color is found with the required parity bit.

STEP 6: The parity bit of a color is determined using the calculation R +G + B mod 2. Therefore if RGB were as follows: (…….1), (…….0), (…….1) and they were added the parity bit would be 0.

STEP 7: The index of the pixel P is then changed to point to the new color i.e. changed to a new pixel value which is pointing to the nearest color. Using this method a pixel is never replaced by a completely different color.

STEP 8: To extract the message M pixels are selected using a pseudo random number generator seeded with a user defined seed. The parity bits of the selected pixels are then read and converted back to the message.

Fridrichs method involves hiding message bits in the parity bit of the index of close colors. For the color of each pixel into which a message bit is to be embedded the closest colors in the palette are searched until a palette entry is found with the desired parity bit. This technique does not change the palette. The parity bits of palette entries of real images are randomly distributed therefore using this method it is never necessary to depart from the original colors too much. This avoids the problem of occasionally having to make large changes in colors, which might indicate that a message has been hidden. Pseudo randomly changing the LSB of a pixel by locating the closest pixel colors in the palette rather than adjusting the palette as with EzStego produces approximately four times less distortion to the carrier image in Fridrich. Fridrich finds the distance between colors whereas EzStego orders the palette by luminance. But instead of searching for the closest colors each time a bit is to be hidden in a pixel the closest colors to each color in the palette with the opposite parity bit is initially chosen. This reduces the problem of having to search through the palette each time a bit is to be hidden. The pixels in which to hide the message are also pseudo randomly chosen.

III CONCLUSION

Although only some of the main image Steganography techniques were discussed in this paper, one can see that there exists a large selection of approaches to hiding information in images. All the major image file formats have different methods of hiding messages, with different strong and weak points respectively. Where one technique lacks in payload capacity, the other lacks in robustness. Least significant bit (LSB) in both BMP and GIF make up for this, but both approaches result in suspicious files that increase the probability of detection when in the presence of a warden.Steganography is a really interesting subject and outside of the mainstream cryptography and system administration that most of us deal with day after day. But it is also quite real; this is not just something that's used in the lab or an arcane subject of study in academia. Steganography has its place in security. It is not intended to replace cryptography but supplement it. Hiding a message with steganography methods reduces the chance of a message being detected. There are an infinite number of steganography techniques. This paper explores a tiny fraction of the art of steganography. It goes well beyond simply embedding text in an image.

Comparison Table 1 shows a summary of the evaluation results presented previously. While some of the results presented previously can be considered to be a little imprecise due to ambiguity in the findings, the effect of unexpected but natural artefacts in images, it is reasonable to draw approximate conclusions with the information available.

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V. REFERENCE

[1] Andersen, R.J. and Petitcolas, F.A.P., "On the limits of steganography", IEEE Journal of Selected Areas in Communications, Special Issue on Copyright and Privacy Protection, 16(4), pp. 474 481, 1998.

[2] Aura, T., “Invisible communication”, Proc. of the HUT Seminar on Network Security „95, Espoo, Finland, November 1995. Telecommunications Software and Multimedia Laboratory, Helsinki University of Technology.

[3] Fridrich, J. and Du, R., “Secure Steganographic Methods for Palette Images”, Proc. The 3rd Information Hiding Workshop, September 28 30, Dresden, Germany, LNCS vol. 1768, Springer-Verlag, New York, pp. 47 60, 1999.

[4] Johnson, N. F. and Jajodia, S., “Steganography: Seeing the Unseen,” IEEE Computer, February, pp.26 34, 1998.

[5] Johnson, N. F. and Jajodia, S., “Steganalysis of Images Created Using Current Steganography Software,” Proc. The 2nd Information Hiding Workshop, Portland, OR, April, LNCS vol.1525, Springer-Verlag, New York, 1998.

[6] Hastur, H., “Mandelsteg,” Software downloadable from http://idea.sec.dsi.uimi.it/pub/security/crypt/codev, 1994.

[7] Westfeld, A. and Pfitzmann, A., "Attacks on Steganographic Systems", Proc. The 3rd Information Hiding Workshop, September 28 30, Dresden, Germany, LNCS vol. 1768, Springer-Verlag, New York, pp. 61 75, 1999.

[8] Provos, N. & Honeyman, P., “Hide and Seek: An introduction to steganography”, IEEE Security and Privacy Journal, 2003 [9] Bender, W., Gruhl, D., Morimoto, N. & Lu, A., “Techniques for data hiding”, IBM Systems Journal,Vol 35, 1996

[10] Petitcolas, F.A.P., Anderson, R.J. & Kuhn, M.G., “Information Hiding – A survey”, Proceedings of the IEEE, 87:07, July 1999

[11] Provos, N. & Honeyman, P., “Hide and Seek: An introduction to steganography”, IEEE Security and Privacy Journal, 2003 [12] Bender, W., Gruhl, D., Morimoto, N. & Lu, A., “Techniques for data hiding”, IBM Systems Journal,Vol 35, 1996

[13] Petitcolas, F.A.P., Anderson, R.J. & Kuhn, M.G., “Information Hiding – A survey”, Proceedings of the IEEE, 87:07, July 1999.

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