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Copy of Image Steganography

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Eng Luis

on 21 February 2013

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Transcript of Copy of Image Steganography

Image Steganography USES OF STEGANOGRAPHY To send news and information without being censored and without the fear of tracing.
It is also possible to simply use steganography to store information on a location.
E-commerce --Biometric finger print scanning, combined with unique session IDs embedded into the fingerprint images via steganography Difference between steganography
and cryptography Steganography
hide the message so there is no knowledge of the existence of the message
comparisons may be made between the cover-media, the stego-media, and possible portions of the message.
The message in steganography may or may not be encrypted. Steganography Techniques Spatial domain
steganography Spatial domain techniques embed messages in the intensity of the pixels directly. Least Significant Bit (LSB) is the first most widely used spatial domain steganography technique. It embeds the bits of a message in the LSB of the image pixels. But the problem with this technique is that if the image is compressed then the embedded data may be lost. Definition 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. Cryptography
Cryptography scrambles messages so it can’t be understood.
With cryptography, comparison is made between portions of the plain text and portions of the cipher text.
The end result in cryptography is the cipher text 1. Spatial Domain
2. Frequency Domain Frequency domain
steganography In frequency domain, images are first transformed and then the message is embedded in the image. When the data is embedded in frequency domain, the hidden data resides in more robust areas, spread across the entire image, and provides better resistance against statistical attacks. There are many techniques used to transform image from spatial domain to frequency domain. The most common frequency domain method usually used in image processing is the 2D discrete cosine transform. LSB algorithm Algorithm to embed text message:-

Step 1: Read the cover image and text message which is to be hidden in the cover image.
Step 2: Convert text message in binary.
Step 3: Calculate LSB of each pixels of cover image.
Step 4: Replace LSB of cover image with each bit of secret message one by one Algorithm to retrieve text message:-

Step 1: Read the stego image.
Step 2: Calculate LSB of each pixels of stego image.
Step 3: Retrieve bits and convert each 8 bit into character DCT algorithm Algorithm to embed message to image

Step 1: Divide the cover image into 8×8 blocks.
Step 2: Perform 2-D DCT on each block.
Step 3: Perform quantization on each block.
Step 4: Perform zigzag scan to convert 8×8 block into one dimensional array.
Step 5: Replace the LSB of DCT coefficients with data bits.
Step 6: Convert 1-D zigzag array back to 8×8 block.
Step 7: Perform Inverse DCT on each block.
Step 8: Combine all the blocks to form stego image. Algorithm to retrieve message(DCT) Step 1: Divide the stego image into 8×8 blocks.
Step 2: Perform 2-D DCT on each block.
Step 3: Perform quantization on each block.
Step 4: Perform zigzag scan to convert 8×8 block into one dimensional array.
Step 5: Check the DCT coefficient.
a) If DCT coefficient is even then data bit is 0 or,
b) If DCT coefficient is odd then data bit is 1.
Step 6: Concatenate the bits to obtain secret message and display it on screen. Performance and result Comparative analysis of LSB based and DCT based steganography has been done on basis of parameters like PSNR. Both grayscale and colored images have been used for experiments. Peak signal to noise ratio is used to compute how well the methods perform. PSNR computes the peak signal to noise ratio, in decibels, between two images. This ratio is used as a quality measurement between two images. If PSNR ratio is high then images are best of quality. Data Hiding Capacity of Image Two Bits Stego
Three Bits Stego
Four Bits Stego
Colour Cycle Stego
PRNG Stego Conclusion Thank You Peak signal to noise ratio PSNR= 20 log(255/sqrt(MSE))
N-1 M-1
MSE=1/(N*M) E E (Pixel Value of cover(i,j)- PV of stego(i,j))
i=0 j=1 PSNR(X,Y) = 10LOG10(Max(Max(x),Max(y))sqr/|x-y|sqr. Some other steganographic techniques

Thank you very much
Today information security is very important for every one (Governments , companies , civilians ) .
Our project provide an image security system with high quality to protect our secrets by using a combination of two type of protection: image scrambling and steganography Conclusion : Findings : [1] Chunlin Li, Guangzhu Xu, Chunxian Song and Jing Jing , “Evaluation of Image Scrambling Degree with Intersecting Cortical Model Neural Network ”
International Journal of Hybrid Information Technology Vol. 5, No. 2,April, 2012, China

[2] Sudhir Keshari, Dr. S. G. Modani , “Image Encryption Algorithm based on Chaotic Map Lattice and Arnold cat map for Secure Transmission ” IJCST Vol. 2, Iss ue 1, March 2011, Jaipur, India

[3] Minati Mishra, Ashanta Ranjan Routray, Sunit Kumar, “ High Security Image Steganography with Modified Arnold’s Cat Map ” , International Journal of Computer Applications (0975 – 8887) Volume 37– No.9, January 2012 ,Balasore,India

[4] J.R. Krenn ,“Steganography and Steganalysis” January 2004

[5] Katherine Struss, “A Chaotic Image Encryption ” , Spring 2009 , University of Minnesota, Morris , USA References : Findings : 1. Hiding a message inside a text
2. Hiding information inside images
3. Hiding information inside audio files
4. ( just for joke ) Hiding bad faith like Tom & Jerry
Steganography types: Steganography :
Steganography, coming from the Greek words stegos, meaning roof or covered and graphia which means writing, is the art and science of hiding the fact (information).

Steganography and scrambling are closely related. scrambles image so they cannot be clear and understood . Steganography on the other hand, will hide the image so there is no knowledge of the existence of the image

Both sciences can be combined to produce better protection of the image. In this case, when the steganography fails and the image can be detected,
it is still of no use as it is encrypted using scrambling techniques. System Description 3 :
Histogram analysis:
An image-histogram illustrates how pixels in an image are distributed by graphing the number of pixels at each color intensity level. We have calculated and analyzed the histograms of the encrypted image and original colored images that have widely different content

. System Description 3 : Image scrambling is a useful approach to secure the image data by scrambling the image into an unintelligible format.

There are many image scrambling algorithms, such as :
1. Arnold Transformation .
2. Magic Square Transformation .
3. MD 5 Algorithm .
4. RC 6 Algorithm .

Because the Arnold transformation has been continuously improved and widely used in practice, so we took Arnold transformation as algorithm To apply in our project . System Description :
Image protection technology is a widely used in recent years, and it is essential to assure information security , so the information will not be easily intercepted .

Currently, the use of computers and networks has grown tremendously, and all computers and networks are being installed, interconnected, to form a global network and internet .

In every day more and more information have been pumped into wired and wireless media over the internet.

This information is not only text, but also multimedia, audio, video and images. Today, images have been widely used therefor image security has become a hot topic. Many crypto system and encryption/decryption techniques have been used to protect the images .

. Introduction : ARNOLD’S CAT MAP :
Arnold‟s cat map (ACM) or Arnold transform (AT), discovered by Russian mathematician Vladimir Arnold in 1960 , is a chaotic map which when applied to a digital image randomizes the original organization of its pixels and the image becomes imperceptible or noisy .

The most important property of Arnold cat map is that it rearranges the position of image pixel, but after iterating a certain numbers it returns the same pixels position as before and thereby produces the original image .

Arnold‟s Cat Map (ACM) is a simple but powerful transform System Description 2 : Image protection system has a two part process . In the first part of process we have focused on scrambling image ( apply the Arnold Cat Map, which changes the position of the pixel values ) .

Most of the work for next second part involves how we can use steganography (hide the scrambling image ) to protect our image .

First process steps :
Design Interface named image protection system using C# language .

Test code for image scrambling and histogram using Matlab .

Convert the code to C# language . Project Procedure : Sender Hacker Receiver
Our project explain and describe how we can keep our information security when we sender it through internet
by using encryption / decryption image and steganography (art of hiding information) technique to protect our image information Project Objectives : Design a System for Image Protection Mixed Between
Image Scrambling and Steganography Department of
Software Engineering Prepared By
Muayad Ahmad Ramadan
Amira Nader Maulood
Nawal Mohammad Kanabi

Supervised by
Mr. Salar Jamal Atroshi
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