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To browse Academia. Skip to main content. By using our site, you agree to our collection of information through the use of cookies. To learn more, view our Privacy Policy. Log In Sign Up. Exploring steganography: Seeing the unseen. Digital technology gives us new ways to apply steganographic techniques, including one of the most intriguing— that of hiding information in digital images. S Neil F. Johnson teganography is the art of hiding informa- with the exception of JPEG images.

All color varia- tion in ways that prevent the detection of hid- tions for the pixels are derived from three primary col- Sushil Jajodia den messages. Steganography, derived from ors: red, green, and blue.

These methods include invisible inks, ues. In many Web pages, the background color is rep- microdots, character arrangement, digital signatures, resented by a six-digit hexadecimal number—actually covert channels, and spread spectrum communica- three pairs representing red, green, and blue. A white tions. Cryptography scrambles a message so blue FF. Its decimal value is , , , and its it cannot be understood.

Steganography hides the mes- binary value is , , , sage so it cannot be seen. A message in ciphertext, for which are the three bytes making up white.

Pixel representation contributes to file size. For exam- In this article we discuss image files and how to hide ple, suppose we have a bit image 1, pixels wide information in them, and we discuss results obtained by pixels high—a common resolution for high- from evaluating available steganographic software. File compression would thus be benefi- represent light intensities at various points pixels. Such an image could contain about Two kinds of compression are lossless and lossy.

Both methods save storage space but have different Digital images are typically stored in either bit results, interfering with the hidden information, when or 8-bit files. A bit image provides the most space the information is uncompressed. A message may be plain tion must remain intact as with steganographic text, ciphertext, other images, or anything that can be images.

Lossless compression is typical of images embedded in a bit stream. Due to the lossy com- instead the use of lossless bit images such as BMP. The most common of these ity digital photographs but not an exact duplicate. In 8-bit color images such as GIF files, each pixel is represented as a single byte, and each pixel merely Embedding data points to a color index table a palette with pos- Embedding data, which is to be hidden, into an sible colors.

The first is the innocent-look- The software simply paints the indicated color ing image that will hold the hidden information, called on the screen at the selected pixel position. Figure 1a, the cover image. Old methods are given new twists. Another ingenious method oughly discounted and ignored. Isman technology has, in fact, sparked a revolu- was to shave the head of a messenger and hard hit.

Blockade issue affects pretext tion in such methods for hiding messages. After the hair grew back, the suets and vegetable oils. For more information on message would be undetected until the techniques for hiding information, see head was shaved again. Early in World War II, lowing, hidden message: steganographic technology consisted almost exclusively of these inks. Kahn, The Codebreakers, Macmillan, written between the lines. Documents can be marked and New York, Documents themselves can hide infor- identified by modulating the position of 2.

Norman, Secret Warfare, Acropolis mation: document text can conceal a hid- lines and words. Zim, Codes and Secret Writing, ciphers unencrypted messages , which development of new technologies that William Morrow, New York, Brassilet et al.

Open coded mes- less conspicuous. February We will see that Figure 1b, the palette for the Renoir cover image, makes a very good cover for holding data. The message may also a b be scattered randomly throughout the image. Representa- image with the message.

Figure 1b shows subtle color changes ital images. Common approaches include palette and b a as well as those that seem drastic.

Each of these techniques can be applied, with varying Pierre-Auguste Figure 2 shows a gray-scale palette of shades. Some degrees of success, to different image files. Least significant bit insertion While gray-scale images may render the best results Least significant bit LSB insertion4 is a common, for steganography, images with subtle color variations simple approach to embedding information in a are also highly effective, as Figure 1 showed.

Unfortunately, it is vulnerable to even a When considering an image in which to hide infor- slight image manipulation. Converting an image mation, you must consider the image as well as the from a format like GIF or BMP, which reconstructs palette.

Obviously, an image with large areas of solid the original message exactly lossless compression to a JPEG, which does not lossy compression , and then back could destroy the information hidden in the LSBs.

Figure 2. Representa- bit images. To hide an image in the LSBs of each tive gray-scale byte of a bit image, you can store 3 bits in each palette of pixel. If you compress the message to be hidden before you embed it, you can hide a large amount of infor- mation. To the human eye, the resulting stego-image will look identical to the cover image. For example, the letter A can be hidden in three pix- els assuming no compression. The original raster data for 3 pixels 9 bytes may be The binary value for A is Inserting the binary value for A in the three pixels would result in 28 Computer.

Figure 3. Traditional steganography conceals information; watermarks extend information and become an attribute The underlined bits are the only three actually changed of the cover image. On average, LSB requires that only half the bits in an image be changed. You can hide data in the least and second least significant bits and still the human eye would not be able to discern it.

Steganogra- phy software authors have devised several approaches— some more successful than others—to hide information in 8-bit images. First, the cover image must be more care- fully selected so that the stego-image will not broadcast the existence of an embedded message.

When information is inserted into the LSBs of the raster data, the pointers to the color entries in the palette are changed. In an abbreviated example, a sim- visually but that may vary by one bit. However, the resulting stego-images as applied 1 01 , 2 10 , and 3 11 , respectively. The raster val- with S-Tools are no longer gray-scale.

Instead of sim- ues of four adjacent pixels of white, white, blue, and ply going with adjacent colors as EzStego does, blue are 00 00 10 Hiding the binary value S-Tools manipulates the palette to produce colors that for the number 10 changes the raster data to 01 00 have a difference of one bit. For example, in a normal 11 10, which is red, white, green, blue.

These gross gray-scale image, white will move to black with the changes in the image are visible and clearly highlight following RGB triples the weakness of using 8-bit images. On the other hand, there is little visible difference noticed between adja- , , Steganography software pro- cesses LSB insertion to make the hidden information After processing with S-Tools, the value for white will less detectable. For example, the EzStego tool arranges be spread over a range of up to eight colors such as the palette to reduce the occurrence of adjacent index colors that contrast too much—before it inserts the , , and message.

This approach works quite well in gray- scale images and may work well in images with related colors. Visually, the stego-image may look the same as the S-Tools, another steganography tool, takes a differ- gray-scale cover image, but it has actually become an ent approach by closely approximating the cover image, 8-bit color image. New colors may not be added to an 8-bit image Masking and filtering techniques, usually restricted due to the palette limit.

Instead, S-Tools reduces the to bit and gray-scale images, hide information by number of colors while maintaining the image quality, marking an image, in a manner similar to paper water- so that the LSB changes do not drastically change color marks. Watermarking techniques may be applied with- values. Visible watermarks are not steganography by defin- Reducing the number of unique colors to 32 ensures ition. The difference is primarily one of intent.

Each of the marks extend information and become an attribute of 32 unique colors in the palette may be expanded to the cover image.

Digital watermarks may include such eight colors having LSB values of the red, green, blue information as copyright, ownership, or license, as RGB triples ranging from to This results shown in Figure 3. In steganography, the object of com- in multiple colors in the palette that look the same munication is the hidden message.

In digital water- February For exam- niche in security is to 3, we increased the luminance of the masked ple, a small message may be painted many times over area by 15 percent.

If we were to change the an image as shown in Figure 3 so that if the stego- supplement luminance by a smaller percentage, the mask image is cropped, there is a high probability that the cryptography, not would be undetected by the human eye. Now watermark can still be read.

A large message may be replace it.


Exploring steganography: Seeing the unseen

Neil F. Johnson 9 Estimated H-index: 9. Estimated H-index: Find in Lib. Add to Collection. Steganography is the art of hiding information in ways that prevent the detection of hidden messages. It includes a vast array of secret communications methods that conceal the message's very existence.


Neural Based Steganography

To browse Academia. Skip to main content. By using our site, you agree to our collection of information through the use of cookies. To learn more, view our Privacy Policy. Log In Sign Up. Exploring steganography: Seeing the unseen. Digital technology gives us new ways to apply steganographic techniques, including one of the most intriguing— that of hiding information in digital images.

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