Steganography and Network Security By Sravya Nagaraju

Contents: Introduction Frame works Categories Image Steganography Applications References

INTRODUCTION 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.

Frame Work:

Categories:

Image Steganography: Image Steganography is the technique of hiding the data within the image in such a way that prevents the unintended user from the detection of the hidden messages or data.

For Example Original image Stego Image Image sources: https://www.pushpraj.com/photos/cool-scenery

Methods: Image Domain Least significant bit Substitution Pixel indicator Stego Color Cycle Max Bit Pixel value Differencing

Image Domain: Images are made up of lots of little dots called pixels. Each pixel is represented as 3 bytes – one for Red, one for Green and one for Blue. 11111000 11001001 00000011 248 201 3 Each byte is interpreted as an integer number, which is how much of that color is used to make the final color of the pixel. 248 + 201 + 3 = Orange Color

The difference between two colors that differ by one bit in either one red, green or blue value is impossible detect for a human eye. So we can change the least significant (last) bit in a byte, we either add or subtract one or more values from the value it represents. This means we can overwrite the last bit in a byte without affecting the colors it appears to be.

A common approach of hiding data within an image file is Least Significant Bit (LSB) Substitution. In this method, we can take the binary representation of the hidden data and overwrite the LSB of each byte within the cover image.

Least significant bit Substitution: Suppose we have the following binary representation for the Cover Image. 10010101 00001101 10010110 00001111 Suppose we want to "hide" the following 4 bits of data: 1011, we get the following, Where the each data bits are accommodated in the least significant bits of each byte of the image.

Least Significant Bit Substitution results in a very minor distortion of the image which is very much negligible for the human eyes. Original Image Stego Image Image source: http://nestopia.com/blog/freshen-house-vibrant-flowers/

Pixel Indicator: This method uses the least two significant bits of one of the channels to indicate existence of data in the other two channels.

Stego Color Cycle: The SCC technique uses the RGB images to hide the data in different channels. It keeps cycling the hidden data between the Red, Green and Blue channels, utilizing one channel at a cycle time.

Max Bit: This method measures the intensity of the pixel and then hides data by random pixel selection with a goal to hide maximum data in each pixel. This method is divided into three parts: Encryption Image Intensity Calculation Steganography.

Original Image Grayscale Image Intense Pixels All Black colored pixels are considered as Intense pixels Image source: http://beartales.me/2013/07/31/old-buildings/

Pixel Value Differencing: Pixel Value Differencing (PVD) is able to provide a high quality stego image in spite of the high capacity of the concealed information. That is, the number of insertion bits is dependent on whether the pixel is an edge area or smooth area. In edge area the difference between the adjacent pixels is more, whereas in smooth area it is less. Smooth Area Edge Area While human perception is less sensitive to subtle changes in edge areas of a pixel, it is more sensitive to changes in the smooth areas

Applications of Image Steganography Secure Private Files and Documents. Hide Passwords and Encryption Keys. Transport Highly Private Documents between International Governments. Transmit message/data without revealing the existence of available message.

References: http://www.garykessler.net/library/steganography.html http://www.jjtc.com/Steganography/ http://www.wikepedia.org/ http://technet.Microsoft.com http://www.bu.edu/

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