Steganography using visual cryptography: Report

STEGANOGRAPHY USING GENETIC ALGORITHM ALONG WITH VISUAL CRYPTOGRAPHY FOR WIRELESS NETWORK APPLICATION

Seminar ReportSubmitted in partial fulfillment of the requirements

For the award of the Degree in

Master of Computer ApplicationsFrom

University of KeralaBy

APARNA N K

DEPARTMENT OF COMPUTER APPLICATIONSMOHANDAS COLLEGE OF ENGINEERING & TECHNOLOGY

Anad, Nedumangadu, Thiruvananthapuram-6955442014

2Dept. of Computer Applications

Steganography

MOHANDAS COLLEGE OF ENGINEERING & TECHNOLOGYAnad, Nedumangadu, Thiruvananthapuram-695544

This is to certify that this is a bonafide report of the seminar presented

by Ms. Aparna N K (Roll No. 1) in partial fulfillment of the requirements for the

award of the degree in MASTER OF COMPUTER APPLICATIONS by the

University of Kerala.

Date……………… Staff In charge

Ms. Jeeja G.S

Asst.professor

Dept of Computer Applications


Steganography

ACKNOWLEDGEMENT

I am greatly thankful to Ms. Sreeja K.( Head of the Department) and

Ms. Jeeja G S (Asst.professor, Department of Computer Applications) for their

kind co-operation for presenting the seminar.

I also extend my sincere thanks to all other faculty members of

Department of Computer Applications and my friends for their co-operation

and encouragements.

Last but not the least I would like the GOD almighty for helping me to

complete my seminar on time.

APARNA N K


Steganography

CONTENTS

Synopsis 5

1. Introduction 6

2. Concepts and principles 7

2.1 About google 7

2.2 Virtual reality 7

2.3 Augmented reality 7

2.4 Project Glass 8

2.5 Android 8

3. Technologies used 9

3.1 Wearable Computing 9

3.2 Ambient Intelligence 9

3.3 Smart Clothing 9

3.4 Eye Tap Technology 10

3.5 Smart Grid Technology 10

3.6 4G Technology 10

4. How it Works? 11

4.1Design 11

4.2Working 12

5. Advantages and Disadvantages 13

5.1 Advantages 13

5.2 Disadvantages 13

6. Future Scope 14

7. Conclusion 15

8. Bibliography 16


Steganography

Synopsis

Image steganography is an emerging field of research for secure data hiding and

transmission over networks. The proposed system provides the best approach for Least

SignificantBit (LSB) based steganography using Genetic Algorithm (GA)along with Visual

Cryptography (VC). Original message isconverted into cipher text by using secret key and

then hiddeninto the LSB of original image. Genetic Algorithm and VisualCryptography has

been used for enhancing the security. GeneticAlgorithm is used to modify the pixel location

of stego image andthe detection of this message is complex. Visual Cryptography isused to

encrypt the visual information. It is achieved by breakingthe image into two shares based on

a threshold.The main aim is to design theenhanced secure algorithm which uses both

steganography using Genetic Algorithm and Visual Cryptography to ensure improved

security and reliability.


Steganography

1. Introduction

Hiding information by embedding secret data into aninnocuous medium is often

referred to as steganography.Steganography can be applied electronically by taking

amessage (a binary file) and some sort of cover (often a soundor image file) and combining

both to obtain a “stego-object”. The rapid development of data transfer through internet

made it easier to send the data accurate and faster to the destination. One of the most

important factors of information technology and communication has been the security of

the information. For security purpose the concept of Steganography is being used.

Steganography is art and science of invisible communication.The steganalysis algorithm

which we used here has the potential to detect thehidden message by the statistic analysis

of pixel values . The use of steganography in combination visual cryptographyis a sturdy

model and adds a lot of challenges to identifyingsuch hidden and encrypted data.


Steganography

2. Concepts and principles

2.1 Steganography

Steganography is the technique of hiding confidential information within any

media. Steganography is often confused with cryptography because the two are

similar in the way that they both are used to protect confidential information. The

difference between the two is in the appearance in the processed output; the

output of steganography operation is not apparently visible but in cryptography

the output is scrambled so that it can draw attention.

Steganography today, however, is significantly more sophisticated than the examples

above suggest, allowing a user to hide large amounts of information within image and audio

files. These forms of steganography often are used in conjunction with cryptography so that

the information is doubly protected; first it is encrypted and then hidden so that an

adversary has to first find the information (an often difficult task in and of itself)

and then decrypt it.

The following formula provides a very generic description of the pieces of the

steganographic process:

Cover medium + hidden data + stego key = stego medium


Steganography

Block diagram of steganography and data transmission

2.2 Steganalysis:

The detection of steganographically encoded packages is called Steganalysis. To

make steganalysis easier, several softwares are readily available on the internet as freeware

or as a shareware. These softwares are capable of determining the irregularity of RGB

patterns in the image, thus alerting the user that the particular image is a stego image.

Steganalysis is the study of detecting messages hidden using steganography; this is

analogous to cryptanalysis applied to cryptography. he goal of steganalysis is to identify

suspected packages, determine whether or not they have a payload encoded into them,

and, if possible, recover that payload.

Based on whether an image contains hidden message, images can be classified into

two classes: the image with no hidden message and the corresponding stego-image (the

very image but with message hidden in it). Steganalysis can thus be considered as a pattern

recognition process to decide which class a test image belongs to. The key issue for

steganalysis just like for pattern recognition is feature extraction. The features should be

sensitive to the data hiding process. In other words, the features should be rather different

for the image without hidden message and for the stego-image.


Steganography

2.3 Cryptography

Cryptography is the practice and study of techniques for secure communication in

the presence of third parties (called adversaries). Cryptography is a cornerstone of the

modern electronic security technologies used today to protect valuable information

resources on intranets, extranets, and the Internet.

.

Cryptography is the science of writing in secret code and is an ancient art; the first

documented use of cryptography in writing dates back to circa 1900 B.C. when an Egyptian

scribe used non-standard hieroglyphs in an inscription. Some experts argue that

cryptography appeared spontaneously sometime after writing was invented, with

applications ranging from diplomatic missives to war-time battle plans. It is no surprise,

then, that new forms of cryptography came soon after the widespread development of

computer communications. In data and telecommunications, cryptography is necessary

when communicating over any untrusted medium, which includes just about any network,

particularly the Internet. Cryptography, then, not only protects data from theft or alteration,

but can also be used for user authentication. There are, in general, three types of

cryptographic schemes typically used to accomplish these goals: secret key (or symmetric)

cryptography, public-key (or asymmetric) cryptography, and hash functions, each of which is

described below. In all cases, the initial unencrypted data is referred to plaintext. It is

encrypted into ciphertext, which will in turn (usually) be decrypted into usable plaintext.


Steganography

2.4 Genetic Algorithm

In the computer science field of artificial intelligence, a genetic algorithm (GA) is a

search heuristic that mimics the process of natural selection. This heuristic (also sometimes

called a metaheuristic) is routinely used to generate useful solutions to optimization and

search problems. A genetic algorithm is one of a class of algorithms that searches a

solution space for the optimal solution to a problem. This search is done in a fashion that

mimics the operation of evolution - a "population" of possible solutions is formed, and

new solutions are formed by "breeding" the best solutions from the population's

members to form a new generation. The population evolves for many generations; when

the algorithm finishes the best solution is returned. Genetic algorithms are particularly

useful for problems where it is extremely difficult or impossible to get an exact solution,

or for difficult problems where an exact solution may not be required. They offer an

interesting alternative to the typical algorithmic solution methods, and are highly

customizable, which make them an interesting challenge for students.


Steganography

2. LSB algorithm 2.1 About LSB algorithm

The proposed scheme uses RSA or Diffie Hellman algorithm to encrypt secret

information. To provide higher security the secret information is encrypted first and

encrypted ASCII value is converted in binary form. In this method the least significant bits of

some or all of the bytes inside an image is replaced with a bits of the secret message.

The image is now used as a cover to embed the encrypted information. The Least Significant

Bit algorithm is faster and reliable and compression ratio is moderate compared to other

algorithms.

Sender Side ::

The image pixels at the same time are also converted into binary form. The image is

now used as a cover to embed the encrypted information. This process is done by LSB

encoder which replaces the least significant bit of pixel values with the encrypted

information bits. The modified picture is now termed as Stego image.


Steganography

Reciever side ::

Upon reception of Stego image the receiver firstly converts the pixels into their

corresponding binary values. The LSB decoder then detaches the encrypted data from image

pixel values. The encrypted data is decrypted using decryption algorithms. This is how, the

plain text is recovered from image.

2.2 Theory of LSB algorithm


Steganography

A typical computer image these days uses 24 bits to represent the color of each

pixel. Eight bits are used to store the intensity of the red part of a pixel

(00000000 through 11111111), giving 256 distinct values. Eight bits are use to store

the green component, and eight bits are used to store the blue component.

2.3 Example


Steganography

5. Proposed System


Steganography

The proposed work is basically a framework designed inMATLAB with two modules

e.g. Steganography usingGenetic Algorithm and Visual Cryptography.An inputimage is

accepted as cover image which is used to hide thesecret message. An input image is

accepted as cover image forthe input message in plain text format. After embedding

thesecret message in LSB (least significant bit) of the coverimage, the pixel values of the

steg-image are modified by the genetic algorithm to keep their statistic characters. This is

also one of the strong algorithmswhich keeps the information proof from any intruder

channel.The simplest way to hide binary data on an image is to usea lossless image format

(such as a Bitmap) and replace theleast significant bits of each pixel in scan lines across the

image with the binary data. This is not secure as an attacker can simply repeat the process

to quickly recover the hidden information.

The proposed system works in the following phases:

SENDERS SIDE ::


Steganography

Encryption Phase: The data to be encrypted is first read from the user through the

keyboard using an appropriate GUI, designed in JAVA. The encryption algorithm used

in the DES.

Encoding Phase:

The encrypted image is then encoded into the least significant bits of the image.

Pixel Modification Phase:

Genetic algorithm is used to modify the pixel locations for enhancing security and

reliability

RECEIVERS SIDE:: Overlapping Phase:


Steganography

The two shares of the same image are needed to retrieve the original information As the cipher data is distributed in both the images, it is impossible for anyone to get the data by

Decoding Phase :

In the decoding phase, the cipher data is decoded from the stego image. The cipher data can be retrieved by the inverse process of encoding process that was employed at the sender side.

Decryption Phase In the decryption phase, the cipher data is converted into the original data.

The DES algorithm is used in the inverse manner using the same encryption key(secret key) as used during encryption of the original data.

6. Algorithm Description


Steganography

The simplest way to hide binary data on an image is to usea lossless image format

(such as a Bitmap) and replace theleast significant bits of each pixel in scan lines across the

image with the binary data. This is not secure as an attacker can simply repeat the process

to quickly recover the hidden information. This technique, known here as “BlindHide”

because of the way it blindly hides information, is also notgood at hiding – the initial portion

of the image is left degraded while the rest remains untouched.

The proposed project work consist of mainly two algorithms which are

o Steganography using GeneticAlgorithm

o Visual Cryptography with Threshold.

Theapplication initiates with Steganography module where thecover image will be

encrypted to generate Stego image. The stagographic image generated in this module will

act as an input for visual cryptographic module.

Algorithm: Steganography

Input: Cover Image

Output: Stego Image

Step 1: Read the cover image.

Step 2: Find out the pixel values of cover image.

Step 3: Read the secret data character wise.

Step 4: Convert each character into its equivalentASCII code.

Step 5: ASCII code is converted into binary values.

Step 6: Enter the secret key.

Step 7: Secret data is converted into cipher data.

Step 8: The stream of 8-bits (cipher data) areembedded into LSB of each pixel of the

cover image.

Step 9: To apply Genetic Algorithm in the stego image the pixel location should be modified.

Algorithm: Visual Cryptography

Input: Stego-Image


Steganography

Output: Encrypted Shares

Step 1: Read Stego-Image generated.

Step 2: The stego image is breaked into three layers namely split-1, split-2, split-3

These three files are containin the hidden data and to get the hidden data

Step 3: The re-assembled picture and the extracted data willbe gained again.

The proposed scheme is based on standard visual cryptography as well as visual secret

sharing. The implementation of the algorithm yields in better result with insignificant shares

when stego images are normally with light contrast. It can also be seen that the algorithm

gives much darker shares in gray output the proposed scheme is based on

standard visual cryptography as well as visual secret sharing. The implementation of the

algorithm yields in better result with insignificant shares when stego images are normally

with light contrast. It can also be seen that the algorithm gives much darker shares in gray

output. This algorithm gives better results in terms of image quality and stegnalysis.

7. Performance Analysis


Steganography

The performance of the proposed system is experimented by performing stegnalysis

and conducting benchmarking test for analysing parameters like Mean Squared Error (MSE)

and Peak Signal to Noise Ratio.

o Cover image : rice.png

o Size : 256*256

o Mean Square Error (MSE) : 0.0678

o Peak Signal-to-Noise Ratio (PSNR) : 59.8188db

After applying Genetic Algorithm the measured performance is shown in below

o Mean Square Error (MSE) : 0.794

o Peak Signal-to-Noise Ratio (PSNR) : 39.4011db

After applying genetic algorithm all the pixel location are altered. Due to the change the

pixel location MSE and PSNR values are increased.

8. Results


Steganography

Encrypt Screen Message to be encrypted: “Sachin Ramesh Tendulkar- The LEGEND”

After clicking on Encrypt Now at the bottom, the encrypted message is shown. CipherText : vbPG8nqjKQoW6N6ugkb4l+wbTz3c+EyRLPkW5nxVv1ZKFxHyPyTQoQ

8. Conclusion


Steganography

The proposed system has discussed implementation of securely using steganography

using genetic algorithm along with visual cryptography. It can be concluded that when

normal image security using steganographic and visual cryptographic technique is applied, it

makes the task of the investigators unfeasible to decrypt the encoded secret message. The

security features of the steganographic are highly optimized using genetic algorithm.

9.Bibilography


Steganography

1) http://en.wikipedia.org/wiki/Stegano_graphy

2) http://www.infoit.org/benefits-/image_hiding

3) http://en.wikipedia.org/wiki/steganalysis

4) http://www.techpark.net/2012/02/29/cryptography

5) http:// ieeexplore.ieee.org/

6) http://en.wikipedia.org/wiki/image _ hiding

7) http://www.webmd.boots.com/hiding /news/20120411/lsb_alg

Steganography using visual cryptography: Report

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Steganography using visual cryptography: Report