AN ANDROID APPLICATION FOR IMAGE

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Date: Name: Prasenjit Kar. Reg.No: 2016015235. Date of Registration: ... Computer Science Department, Sharda University who inspired me for this project, ...
AN ANDROID APPLICATION FOR IMAGE STEGANOGRAPHY

A DISSERTATION REPORT

Submitted by PRASENJIT KAR

In partial fulfillment for the award of the Degree of MASTER OF TECHNOLOGY

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

SCHOOL OF ENGINEERING AND TECHNOLOGY SHARDA UNIVERSITY, GREATER NOIDA-201306

MAY - 2018

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DECLARATION I hereby declare that this report submission is my own work and that, to the best of my knowledge and belief, it contains no material previously published or written by another person nor material which has been accepted for the award of any other degree or diploma of the university or other institute of higher learning, except where due acknowledgment has been made in the text.

Place: Greater Noida

Signature of the candidate

Date:

Name: Prasenjit Kar

Reg.No: 2016015235 Date of Registration:

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CERTIFICATE Certified that this project report titled “AN ANDROID APPLICATION FOR IMAGE STEGANOGRAPHY” is the bonafide work of Mr. Prasenjit Kar who

carried out project work

under my supervision. Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate.

Signature of Supervisor Name: Rajiv Kumar Designation: Ph.D in Computer Science School of Engineering & Technology (SET) Sharda University, UP, India

Signature of Co-Supervisor Name: Pradeep Kumar Mishra Designation: Ph.D in Computer Science School of Engineering & Technology (SET) Sharda University, UP, India

Signature of Program Coordinator Name: Place: Date:

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ABSTRACT Image Steganography is mainly used for hiding an image or secret message in a cover image. For data hiding this technique is being widely used for so many years. Image steganography is being used now by government, individual sender and receiver, in business and in so many fields. Now-A-Days this process has become very popular world wide. People are doing research on image steganography and inventing new algorithms for image steganography. Hiding data in cover image by modifying bits of that is now optimized by so many new algorithms. Enthusiastic people are increasing demand of researching on image steganography and developing pc software and mobile application using different developing tools, programming languages and their own invention, algorithms etc.

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ACKNOWLEDGEMENT First and foremost I thank my supervisor Dr. Rajiv Kumar, Associate Professor, Computer Science Department, Sharda University for his guidance, cooperation, dedication and support. I would like to thank my co-supervisor Dr.Pradeep Kumar Mishra, Assistant Professor, Computer Science Department, Sharda University who inspired me for this project, gave me relevant guiding, kept me on the correct path and allowed me to carry out my research work successfully. I would like to honor my institute Sharda University, Greater Noida. I am also very grateful to sir Mr.Diwakar Gautam, Our Head of Department Dr.Ashok Kumar Sahoo, Our Dean Dr.Parma Nand and vice chancellor of Sharda University Prof.Brishbhan Singh Panwar and all the faculty members and friends. Finally, I would like to gratefully and sincerely thank to my parents for their love and encouragement, without whom I would never get this opportunity. This research work gave me a significant amount of practical knowledge which will be valuable for my lifetime. Being a hot topic these days, this research work gave me an upward trust in my relevant fields.

Prasenjit Kar

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PREFACE To achieve secure communications, the cousins cryptography and steganography are used. The former scrambles secret messages in such way that only the intended recipient is capable of unscrambling them. The latter seeks to hide a secret message inside an innocuous message, audio, image, or video file (called the cover medium), in such a way that eavesdroppers will not suspect the very existence of the secret message. Combined, cryptography and steganography provide a secure form of communication: The former will encode the secret message in such a way that even if it intercepted, it is hard decrypt it; the latter will hide the encoded secret message. Images are the most popular cover medium used in steganography. Many different image file formats exist, most of them for specific applications. There are different steganographic algorithms for different image formats. In this work, using the idea of splitting the cover image into several bit planes, I propose to hide secret messages in the intersection points of those planes with certain geometric objects. The resulting image containing the message is called stego-image. The file stego image should be such that a third party intercepting it will not have any indication that a secret message is present in the image. Our technique has been implemented in Android platform.

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LIST OF FIGURES Figure 1: General Steganography Process .................................................................................................. 11 Figure 2: Image Steganography Process ..................................................................................................... 12 Figure 3: Types of Steganography ............................................................................................................... 15 Figure 4: A .png Format File ........................................................................................................................ 16 Figure 5: LSB Steganography....................................................................................................................... 22 Figure 6: LSB Insertion Effect ...................................................................................................................... 24 Figure 7: MSB Insertion Techniques ........................................................................................................... 25 Figure 8: Project App................................................................................................................................... 27 Figure 9: Encoding Process ......................................................................................................................... 28 Figure 10: Decoding Process ....................................................................................................................... 29 Figure 11: App folder in SD card ................................................................................................................. 30 Figure 12: Home Screen .............................................................................................................................. 31 Figure 13: Encoding Screen ......................................................................................................................... 32 Figure 14: Saving password for later using ................................................................................................. 32 Figure 15: Decoding Screen ........................................................................................................................ 33 Figure 16: Receiver Screen.......................................................................................................................... 34 Figure 17: About app Screen ....................................................................................................................... 34 Figure 18: App icon ..................................................................................................................................... 48

LIST OF TABLES Table 1: Comparison between JPEG and PNG ............................................................................................ 17 Table 2: Data Collected after Testing of Project ......................................................................................... 47

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LIST OF SYSMBOLS, ABBREVIATION & NOMENCLATURE 

Least Significant Bit (LSB)



Steganalysis,



Stego-images



Image Quality Metrics (IQMs)



Simple Columnar Transposition technique with multiple rounds (SCTMR)



External memory card in mobile phone (SD card)



Text format of image before converting to binary (base64)

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CONTENTS DECLARATION .......................................................................................................................................... 2 CERTIFICATE ............................................................................................................................................. 3 ABSTRACT.................................................................................................................................................. 4 ACKNOWLEDGEMENT ............................................................................................................................ 5 PREFACE ..................................................................................................................................................... 6 LIST OF SYSMBOLS, ABBREVIATION & NOMENCLATURE ......................................................... 8 CHAPTER 1 ............................................................................................................................................... 11 INTRODUCTION ...................................................................................................................................... 11 1.1 MOTIVATION ................................................................................................................................. 11 1.2 AIM ................................................................................................................................................... 12 1.3 OBJECTIVES ................................................................................................................................... 12 1.4 EXPECTED OUTCOME ................................................................................................................. 12 1.5 EVALUATION CRITERIA ............................................................................................................. 13 1.6 STRUCTURE OF DISSERTATION................................................................................................ 13 1.7 OUTLINE OF THESIS ..................................................................................................................... 13 CHAPTER 2 ............................................................................................................................................... 14 LITERATURE REVIEW ........................................................................................................................... 14 2.1 TYPES OF STEGANOGRAPHY .................................................................................................... 14 2.2 WHAT IS AN IMAGE ..................................................................................................................... 15 2.3 TYPES OF IMAGE .......................................................................................................................... 15 2.3.1 JPEG .......................................................................................................................................... 15 2.3.2. PORTABLE NETWORK GRAPHICS (PNG) ......................................................................... 16 2.4 AN OVERVIEW OF LSB ................................................................................................................ 18 2.4.1 ADVANTAGES OF LSB .......................................................................................................... 20 2.4.2 DISADVANTAGES OF LSB ................................................................................................... 20 2.4.3 THE LSB ALGORITHM........................................................................................................... 20 2.4.5. LSB IN JPEG IMAGE FORMAT ............................................................................................ 21 2.4.6 IMPROVED LSB METHOD FOR 24 BIT COLOR IMAGES ................................................ 23 2.4.7 LSB METHOD FOR 8 BIT COLOR IMAGE .......................................................................... 24

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2.5 MSB STEGANOGRAPHY .............................................................................................................. 24 2.5.1 ALGORITHM FOR MSB STEGANOGRAPHY ..................................................................... 26 CHAPTER 3 ............................................................................................................................................... 28 METHODOLOGY ..................................................................................................................................... 28 CHAPTER 4 ............................................................................................................................................... 30 DESIGN & IMPLEMENTATION ............................................................................................................. 30 CHAPTER 5 ............................................................................................................................................... 35 RESULT AND ANALYSIS ....................................................................................................................... 35 CHAPTER 6 ............................................................................................................................................... 49 CONCLUSION ........................................................................................................................................... 49 REFERENCES ........................................................................................................................................... 50 APPENDIX ................................................................................................................................................. 52

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CHAPTER 1 INTRODUCTION 1.1 MOTIVATION Data hiding is a popularly used technique for secure communication. Data hiding is the technique of embedding information into digital content without causing perceptual degradation. Watermarking, cryptography and steganography are three famous techniques used in data hiding. Steganography is an ancient science for hiding the information in the communication [1]. Steganography is defined as a technique for concealing information and it is applied in the area of the computers and networks widely.

Figure 1: General Steganography Process

There are different types of steganography processes like steganography for hiding data in a text, steganography for hiding data in an image, steganography for hiding images in an audio, steganography for hiding images in a video, steganography for hiding images in a protocol etc. Among them image steganography is the mostly used technique now-a-days. Image Steganography is defined as a hiding process of a secret message within an image in 11

such a way that others cannot understand the presence of contents of the hidden message.

Figure 2: Image Steganography Process

1.2 AIM Now-a-days a lot of software and mobile apps are being developed using deferent algorithms for performing image steganography process. Here we are going to develop an android application which can be used for image steganography process.

1.3 OBJECTIVES Using this app we will try to hide a message by a cover image. Here we shall try to add data bits of message within data bits of image. There can be change in image but image must be shown. A password will be used for recovery in receiver site. The password will be set by the encoder. If only that password is given than the original message and image will be shown because by giving the input of password the data bits of message will be extracted from data bits of image. By this process the original image will be recovered. The secret message will be revealed to receiver. Thus only intended users will be able to reveal secret messages.

1.4 EXPECTED OUTCOME Expected outcome will be to reveal the secret message which was encoded by encoder within a cover image. Data bits will be changed by performing the encoded process and the 12

message will be no more showing in any format .txt or image anything. The message will be fully vanished. Only by inputting of a password the expected message in its original text format will be shown.

1.5 EVALUATION CRITERIA Evaluation or implementation of our project application will be done by android programming language. Algorithms will be used for encoding and decoding processes.

1.6 STRUCTURE OF DISSERTATION The full dissertation work will contain full implementation of a technique which can be used for image steganography. A fully new android app will be designed with new algorithms and techniques. Android programming codes will be written for building our apk file. We shall try to have less limitations for using the app. Our target will be to use the app in android versions as more as we can. Message sending will be more and more secure after this app is built. The app will be more reliable than previous app and softwares were built for image steganography process by researchers and developers.

1.7 OUTLINE OF THESIS 

Chapter 2 contains literature reviews collected from various conference paper and international journals. Many kinds of techniques for image steganography process have been used by researchers published in international science journals and conferences.



Chapter 3 contains the methodology we have used in our app, algorithm for our used techniques, flowcharts shows flow of the whole steganography process.



Chapter 4 contains the design and implementation of our project app. Platform and languages used for project.



Chapter 5 contains the results or outcomes of the project.



Chapter 6 contains the conclusion for the whole thesis and project works.

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CHAPTER 2 LITERATURE REVIEW Steganography is a process mainly used in the purpose of concealing files, messages, images, or videos within another files, messages, images, or videos. The word “steganography” is formed by combining two keywords i.e. steganos(στεγανός), which means "covered or concealed" and graphein (γράυειν) which means "writing"[2] thus, it can be referred and can art of writing which is covered by another object in our case which is an image. Image can be hide in image where one image will be called cover image and another image will be called sink image. But if we want to enclose a message into an image array we need that two files - image and message. That image will be used to grip the whole message. Generally that image is called a ‘cover image’. The second file is that message which will be griped by or hidden into that so called cover image. When the enclosing process will begin the cover image and the message together will make a mixture by mixed with one another. We give the mixture a name, an ‘stego image’. That single stego image will be decoded later by decoding process. A new stego key (a type of password) can also be used to hide then later decode. Most of the recommended image files are ‘.bmp’ image files (bitmap file). Lossless 24 bit image files which have a ‘.bmp’ extension is used for the most of the times. Then for the second best image file we choose a gray image file with 256 color. But bitmap files are used frequently for better performance and quick generated result output. Generally images are combination of pixels which are represented by three bytes, one for red, one for green, one for blue [3]. The combination makes a final color.

2.1 TYPES OF STEGANOGRAPHY Normally we categorize steganography on the basis of the medium used as a covering agent [1]. It can be broadly divided into some types given below: 

Image Steganography



Text Steganography



Audio Steganography 14



Video Steganography

Figure 3: Types of Steganography

2.2 WHAT IS AN IMAGE An image (Latin name: imago) is mainly an artifact that depicts or records visual perception [4]. Amusing fact is that for a computer it is nothing but the 2-D representation of the real world objects which is digitized by computer and is represented over a 2-D plane with pixels as tiny co-ordinates, combination of which forms the whole image [5]. The pixels are the smallest picture element which forms the real image. Each pixel stores the intensity value in the form of bits. Normally the number of bits for each and every pixel is known as Bit Depth [6]. Monochrome and grayscale images use 8 bits for each pixel and these are able to display 256 different colors or shades of grey whereas for a color image having RGB model areusually combination of 24 Bits [7]. Depth is needed 24 bits (8 bits for each color component) to store each pixel which is a synonym of True color [8]. Thus in every given pixel, there can be 256 different quantity of colors like red, green and blue, adding up to more than 16-million combinations results in more than 16-million colors [9]. The larger amount of colors that can be displayed, the larger the file size must be noticed.

2.3 TYPES OF IMAGE Images are categorized into various formats, each of them has its own characteristics, advantages and disadvantages. Some of the popular formats used now-a-days are PNG, JPEG, JIFF, BMP, GIF etc. Among them all two formats are discussed here. 2.3.1 JPEG The most well known format JPEG is an abbreviation for "Joint Photographic Experts 15

Group," which is also the name of the committee, developed this popular image format. JPEG is generally a compressed image file format which consists of a huge array of colors which makes it the best choice for compressing technique of photographic images. It is a popular format used for many times in our day to day life. Though a JPEG image is a high resolution image which has high color depth and clarity but one thing about it that it is a lossy format which means some quality is lost if the image is compressed[10]. After each compression is done, the image losses its original form. After a certain amount of compression, the image completely losses its integrity. Then it appears as block of colors just like lego pieces. Some common properties of JPEG can be like: 

A very popular format for all imaging devices.



It’s a compressed format.



JPEG format allows a wide range 8-24 bits indexed color.



Generally uses lossy compression algorithms.

2.3.2. PORTABLE NETWORK GRAPHICS (PNG)

PNG, stands for Portable Network Graphics is a very popular image format used over the internet. This format was developed to overcome the drawbacks of a GIF file format image [4]. It supports generally a palette based image which means 24 bits for RGB and 32 bits for ARGB where A stands for an alpha channel of that image. This format was specifically designed for internet usage thus it does not support other color model apart from RGB. It provides lossless compression, thus providing real image after every compression.

Figure 4: A .png Format File

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Some very common properties of PNG format file can be like: 

A popular format for usage over the internet.



Lossless Compression Algorithms are used in this.



Only RGB models are applicable.



It provides 24 or 32 bit depth for images.

JPEG

PNG

Joint Photographic

Portable Network

Expert Group

Graphics

File Size

Small

Larger than JPEG

File Suffix

.jpg

.png

Resolution

High

High

Support Color

16 Million Colors

Much Higher in 32

File Type

bit Complexity

Quite Complex

Comparatively Simpler

Ideal For

Camera

Internet

Color Depth

8-24 bits

24-32 bit

Compression Algorithm

Lossy

Lossless

Table 1: Comparison between JPEG and PNG

Image-based steganography technique is broadly divided into two categories: 

Frequency domain Steganography



Spatial domain steganography.

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The first digital image steganography was done in the spatial domain using LSB coding which replaces the least significant bit or bits with embedded data bits[8]. JPEG transforms spatial data into the frequency domain [3] and employs a lossy compression thus, on each processing step and conversion step back to spatial domain, the image losses its integrity due to so much noise and loss of data. These would be hard to correct using error correction coding. Hence, it was concluded that steganography would not be possible in JPEG images.JPEG encoding is divided into lossy and lossless stages [1]. DCT transformations to the frequency domain and quantization stages are lossy, whereas entropy encoding of the quantized DCT coefficients (which we will call the JPEG coefficients to distinguish them from the raw frequency domain coefficients) is lossless compression [3] and researchers took advantage of this property of JPEG and decided to embed data bits inside the JPEG coefficients before the entropy coding stage. Among bytes of image we can change least significant bit which means the last bit of a byte means we can overwrite the last bit which will not affect the color of the cover image. Thus binary representation of message or data can be hidden in the cover image data [2]. This is LSB technique.

2.4 AN OVERVIEW OF LSB A digital image is a 2 Dimensional array of varying intensity levels. For gray scale image, 8 bits per pixel are used whereas in a color image following RGB model, there are 24 bits/pixel, 8 bits assigned to each color components. Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover image [5]. The LSB uses a simple concept of replacing the last bit with the message bit. An 800 × 600 pixel image, can thus store a total amount of 1,440,000 bits or 180,000 bytes of embedded data [9]. For example a grid for 3 pixels of a 24-bit image can be as follows: (00101101 00011100 11011100) (10100110 11000100 00001100) (11010010 10101101 01100011) When the number 200, which binary representation is 11001000, is embedded into the least significant bits of this part of the image, the resulting grid is as follows: (00101101 00011101 11011100) (10100110 11000101 00001100) (11010010 10101100 01100011) Although the number was embedded into the first 8 bytes of the grid, only the 3 underlined bits needed to be changed according to the embedded message. On average, only half of the bits in an image will need to be modified to hide a secret message using the maximum cover size [10]. 18

Since there are 256 possible intensities of each primary color, changing the LSB of a pixel results in small changes in the intensity of the colors. These changes cannot be perceived by the human eye - thus the message is successfully hidden. With a well-chosen image, one can even hide the message in the least as well as second to least significant bit and still not see the difference [5]. The advantage of LSB embedding is its ease and many techniques use these methods [5]. But, if the security aspect is considered it may not be a good choice due to its low robustness and tamper resistance. They are highly sensitive to any sort of image processing like cropping, filters, resizing, contrasting etc. In the case of 24 bit color image each pixel is composed of RGB values and each of these colors requires 8-bit for its representation. R (8 bits), G (8 bits) , B (8 bits)]. If we read color image in Matlab and display its first pixel, we get : >> a = imread(‘coverimage.jpg’) >>a (1,1,1) = 220 >>a (1,1,2) = 198 >>a (1,1,3) = 135

Here last term (1, 2 and 3) represent RGB component of pixels (1,1) So RGB first pixel can be represent as [11011100 11000110 10000111]

For embedding secret image whose first pixel is [11001001] firstly we have to replace last 2 LSB of each of RGB component and then embedding first 2 MSB of first pixel of secret image to R component, then next 2 MSB of first pixel of secret image to G component and lastly another next 2 MSB of first pixel of secret image to B component. In this way we get stego image whose first pixel is:

[11011111 11000100 100000110].

In this method 6 bits of secret image get hide by replacing only 2 bits of RGB component so stego-image is visually indistinguishable from the original cover-image in the case of 24 bit. 19

2.4.1 ADVANTAGES OF LSB 

LSB algorithm is it is quick and easy to implement.



Causes minimal distortion per unit area of image.



LSB insertion also works well with gray-scale images

2.4.2 DISADVANTAGES OF LSB 

It contains low robustness.



Highly vulnerable for cropping, contrasting and other sort of image processing.

2.4.3 THE LSB ALGORITHM

Algorithm for encoding 

Read the cover image and text message, which is to be hidden in the cover image.



Convert text message in binary.



Calculate LSB of each pixel of cover image.



Replace LSB of the cover image with each bit of secret message one by one.



Write stego image. Algorithm to retrieve text message



Read the stego image.



Calculate LSB of each pixel of stego image.



Retrieve bits and convert each 8 bit into character.

2.4.4. LSB IN PNG IMAGE FORMAT PNG format image file for a LSB Steganography is a great choice now-a-days. As the LSB works on spatial domain thus, it becomes very important that there is no introduction of noise or error of any sort. Under the scenario .png is the best format due to the fact that it uses a lossless compression so the substitutions made during the whole process of LSB steganography is not lost. PNG also provides huge storing capacity and high quality image 20

after steganography thus, avoiding detection by just looking at the image. 2.4.5. LSB IN JPEG IMAGE FORMAT For a JPEG image, LSB is similar to what is done in LSB for PNG with a slight difference that they are entropy encoded. For example, the image of data uses LSB[10] to hide first eight bytes of three pixels[3].

Obtained Pixels: 00100111 10101011 111000001 11101001 00011001 001110100 00101010 11111110 111000111 Data: 10101010 Result Pixels: 00100111 10101010 111000001 11101000 00011001 001110100 00101011 11111110 111000111

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Figure 5: LSB Steganography

Another technique is MSB technique. In LSB we have to overwrite right most bits of bytes whereas in MSB we have to overwrite leftmost bits of bytes. There are also other techniques like masking and filtering, transform technique etc which can be used in different ways for steganography process. But we have to keep in mind that all of the techniques of steganography process have some limitations. Associate improvement within the plain LSB based image steganography can be implemented by the use of bit inversion technique to improve the stego image quality[5]. Two schemes of bit inversion techniques can be implemented. In these techniques, LSBs of some pixels of canopy image are inverted if they occur with a particular pattern of some bits of the pixels. In this way, less variety of pixels are dissimilar in comparison to plain LSB method. So that we can say that PSNR of our stego image has been improved now. For accurate de-steganography, bit patterns for which LSBs has inverted must be hold on at intervals the stego image somewhere. The proposed bit 22

inversion technique provides good improvement to LSB steganography. 2.4.6 IMPROVED LSB METHOD FOR 24 BIT COLOR IMAGES In this method a cover image is actually a 24 bit color image. The cover image should be split into its 3 plane (red, green, blue). The main aim of this method is hiding most of the secret image bits in blue plane rather than red and green. Blue plane is selected because a research was conducted by Hecht, according to which 65% of all cones of human eyes are sensitive to red color, 33% are sensitive to green color, and only near about 2 % are sensitive to blue color, as a result visual perception of intensely blue objects is less distinct that the perception of objects of red and green.

Steps to be carried out in this technique and implement in MATLAB are: 

Select the cover image, multiply the red plane by 254 to make last bit 0: by “bitand(c(x,y,1), uint8(254))” command. Obtain first MSB i.e. 8th bit of secret image and then embedded it in last LSB of red plane



Now take green plane of cover image and convert its last 2 LSBs to 0 by “bitand” command, multiplying each pixel with 252 : “bitand(c(x,y,2), uint8(252))”. Obtain next to MSB i.e 7th and 6th bit of secret image and embedded it into green plane.



Lastly take blue plane of cover image and convert its last 3 LSBs to 0 by “bitand” command multiply each pixel by 248: “bitand(c(x,y,3), 248)”. Obtain next 3 MSB i.e. 5th, 4th and 3rd bit of secret image and embedded it into blue plane So if 24 bit color image first pixel is represent as [11011100 11000110 10000111]

Then for embedding secret image whose first pixel is [11001001], we follow above step and get stego image whose first pixel is: [11011101 11000110 100000010].

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2.4.7 LSB METHOD FOR 8 BIT COLOR IMAGE First we have to consider an 8-bit color image where each pixel is stored as a byte representing a grayscale value. Suppose the first three pixels obtained from the original image have the following values:

[11 00 1001 11011110 11101001] And pixels of secret image is: [11100101 10110110 11110001] First we have to remove the last 4 LSB of cover image by multiplying each pixel with [11110000]. In Matlab it is done by using “bitand” command which gives result - original image pixels [11000000 11010000 11100000]. After shifting of secret image pixels bits by 4 toward right and after that adding with original cover image pixel by using “bitor” command we perform this process.

Last 4 LSB of cover image then get replaced by first 4 MSB of secret image and thus we get stego image whose first three pixels are: [11001110 11011011 11101111]

Figure 6: LSB Insertion Effect

2.5 MSB STEGANOGRAPHY MSB is highest bit in a series of numbers in binary. e.g in the binary number : 11001100, the 24

most significant bit is far left 1. In the MSB technique the secret message is embedded in the most significant bit of the pixel of the image.240 can be hidden in the first eight bytes of three pixels in a 24 bit image.

PIXELS:

00100111 11101001 11001000 00100111 11001000 11101001 11001000 00100111 11101001

240: 011110000

RESULT:

00100111 11101001 11001000 10100111 11001000 01101001 01001000 00100111 01101001

Figure 7: MSB Insertion Techniques

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2.5.1 ALGORITHM FOR MSB STEGANOGRAPHY

Algorithm for encoding 

Read the cover image and text message, which is to be hidden in the cover image.



Convert text message in binary.



Calculate MSB of each pixel of cover image.



Replace MSB of the cover image with each bit of secret message one by one.



Write stego image.

Algorithm to Retrieve Text Message 

Read the stego image.



Calculate MSB of each pixel of stego image.



Retrieve bits and convert each 8 bit into character.

Steganography technique using Daubechies Discrete Wavelet Transform (DWT) process can also be implemented in some way[6]. For this technique, what we have to do is first the cover image is to be reworked with the help of DWT and then secret information should be embedded with coefficients of Daubechies-DWT which will provide astego image as an output[11]. After that, reverse process can be applied to obtain the secret information back from the generated stego image. Least Significant Bit (LSB) which is based on image steganography, improves the existing LSB substitution techniques for boosting of the protection level of hidden information can be considered as the best approach. To substitute LSB of RGB true color image it is brand spanking. This new security conception can hide secret information at intervals of the LSB of image where a secret key encrypts the hidden information to protect it from unauthorized user’s access.

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Figure 8: Project App

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CHAPTER 3 METHODOLOGY For image steganography process in our android app we have done our works using some procedures. There are encoding step and decoding step. Procedures we have used are given below like algorithms: 

Algorithm for Encoding :

1. Read a cover image and a text message. 2. Convert cover image and text message into base 64 format. 3. Delete last 4 bits of the base 64 format data of cover image. 4. Calculate number of rest of the bits of base 64 format data of the cover image. Name it Pj 5. Add the text message there at the end of the base 64 format data of image. 6. Write stego image.

Insert Cover

•base64 fomat •binary format

Image •base64 format Enter Secret •binary format Message

Delete last 4 bits from base64 image data

This forms a stego image (message+ image)

Add the base64 message data at the end of the remaining bits Figure 9: Encoding Process

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Algorithm for Decoding :

1. Read the base64 data of stego image 2. Calculate the number of the bits of base 64 bit format data of stego image. Name it Qj. 3. Subtract Pj from Qj.Name it Msglen. 4. After knowing the Msglen we can easily retrieve the secret message from Qj.

For decoding process we input the base64 format data of stego image. Then we calculate length of that data ( image + message ). Then we consider base64 format data of cover image. We calculate length of that data ( image ). Then we decrease 4 bits from image data. Thus we get a result. Then from ( image + message ) base64 data we subtract the result. Thus we get another result. Then we replace bits for that result with base64 data of image-message or sink image. After some reverse steps and bit replacement steps we get the base64 data of our secret message. These are all done in decoding part. Then in receiver part the base64 message data is converted to original text by string conversion mechanism.

Calculate • base64 ( Image Length

+ Message )

Decrease 4 bits from base64 format (image + message)

Calculate • base64 ( Length

Image)

Base 64 format of original message

Reverse steps

Figure 10: Decoding Process

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Bits replaceme nt steps

CHAPTER 4 DESIGN & IMPLEMENTATION We have designed our project app with android studio. Here minimum sdk version 15 is uesd. Target SDK version is API 26 : Android. Gradle version is 3.3. Android Plugin version used is 2.3.3. Android phones can use this app with minimum android version 4.0.3 (IceCreamSandwich). Lower version of android like version 4.0 or lower cannot use this app. So users must have an android phone with android version 4.0.3 or higher to use this app in their android phone. For testing 'image steganography' process user can use small size of image to run the app smoothly without any delay." There are 5 screens in our app contains a lot of calculations, inputs etc. At the time of running this app a folder named “ Image Steganography ” will be created automatically and all the files will be saved there when other process will be executed time to time.

Figure 11: App Folder in SD card

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Home Screen: In home screen we insert a cover image and enter the secret message that we want to send to the receiver.

Figure 12: Home Screen

Encoding Screen: In encoding part we have to perform a lot of calculations which will be done automatically inside the app and the encoded stego image or image-message base64 data will be saved in memory card of our mobile phone in .txt file.

31

Figure 13: Encoding Screen

We have to input password for using later in decoding part. Now this password will remain saved in memory card of our mobile phone in .txt format.

Figure 14: Saving password for later using

32

Decoder Screen: In decoding part decoding works are done. We have to input a password. A process will try to match the password with the previously saved password done in encoding part in encoding screen.

Figure 15: Decoding Screen

Receiver Screen: If both of the password matches one - given input from decoding screen and another - saved in encoding screen, then only receiver screen can be reached otherwise error message will be shown everytime that the password should be input like previously saved one.In receiver screen the original cover image and the secret message will be revealed.

33

Figure 16: Receiver Screen

About app Screen: In these screen we just say about our app.

Figure 17: About app Screen

34

CHAPTER 5 RESULT AND ANALYSIS For observing results we have tested it practically in an android handset. With 5 test images we have tested for various messages. The characteristics of smart phones used for testing: Used Model :SYMPHONY XPLORER ZV Android Version: Android v4.4.2 KITKAT Processor: Octa core 1.4 GHz ROM: 16GB The characteristics of the cover image: Type: JPG file Dimension: 4 KB Pixel arrangement: 8x8 Test images used for cover image: - 8 pixel blue.jpg - 8 pixel brown.jpg - 8 pixel gray.jpg - 8 pixel pink.jpg - 8 pixel red.jpg

- myphoto.jpg – Dimension (100px x 100px) The characteristics of the secret message: The message can be of any size but if message length is less than 100 characters then it works better with this app . 35

Runtime: less than 1 second. For using large size image like myphoto.jpg given above it takes 3-4 seconds. For example here we have inserted a cover image of 8 pixel red ( )

and entered a secret

message – “Today is workers day ”. Then we have to calculate base64 format data and binary data for both. Then we delete last 4 bits of base64 string obtained from image. Then the string base64 data of text “ Today is workers day ” is added after that. Thus a string will be formed. This string forms a stego image or sink image ( message + image ).

Base64 Data

Secret Messag e Today is workers day VG9kY XkgaX Mgd29y a2Vycy BkYXk =

Cover Image

Stego Image

8 x 8 dimension containing 8 pixel red jpeg image ( )

Red color image

/9j/4AAQSkZJRgABA QAAAQABAAD/2wB DAAoHBwgHBgoICA gLCgoLDhgQDg0NDh 0VFhEYIx8lJCIfIiEmK zcvJik0KSEiMEExNDk 7Pj4+JS5ESUM8SDc9P jv/2wBDAQoLCw4Nh wQEBw7KCIoOzs7Ozs 7Ozs7Ozs7Ozs7Ozs7Oz s7Ozs7Ozs7Ozs7Ozs7O zs7Ozs7Ozs7Ozs7Ozs7 Ozv/wAARCAAIAAg DASIAAhEBAxEB/8Q AHwAAAQUBAQEBA QEAAAAAAAAAAAE CAwQFBgcICQoL/8A tRAAAgEDAwIEAwF BAQAAAF9AQIDAQ RBRIhMUEGE1FhByx FDKBkaEII0KxwRVSf AkM2JyggkKFhcYGRolJ icoKSo0NTY3ODk6Q0R FRkdISUpTVFVWV1hZ WmNkZWZnaGlqc3R 1dnd4eXqDhIWGh4i

/9j/4AAQSkZJRgAB AQAAAQABAAD/2 wBDAAoHBwgHBgo ICAgLCgoLDhgQDg 0NDh0VFhEYIx8lJCI fIiEmKzcvJik0KSEi MEExNDk7Pj4+JS5E SUM8SDc9Pjv/2wBD AQoLCw4NDhwQEB w7KCIoOzs7Ozs7Ozs 7Ozs7Ozs7Ozs7Ozs7 Ozs7Ozs7Ozs7Ozs7O zs7Ozs7Ozs7Ozs7Ozs 7Ozv/wAARCAAIA AgDASIAAhEBAxE B/8QAHwAAAQUB AQEBAQEAAAAAA AAAAAECAwQFBg cICQoL/8QAtRAAAg EDAwIEAwUFBAQ AAAF9AQIDAAQR BRIhMUEGE1FhByJ xFDKBkaEII0KxwR VS0fAkM2JyggkKFh cYGRolJicoKSo0NT Y3ODk6Q0RFRkdIS

36

JipKTlJWWl5iZmqKjp KWmp6ipqrKztLW2t7i 5usLDxMXGx8jJytLT1 NXW19jZ2uHi4+Tl5ufo 6erx8vP09fb3+Pn6/8QA HwEAAwEBAQEBAQ EBAQAAAAAAAAEC AwQFBgcICQoL/8QAt REAAgECBAQDBAcF BAQAAQJ3AAECAxE EBSExBhJBUQdhcRMi MoEIFEKRobHBCSMz UvAVYnLRChYkNOEl 8RcYGRomJygpKjU2N zg5OkNERUZHSElKU 1RVVldYWVpjZGVmZ 2hpanN0dXZ3eHl6goOE hYaHiImKkpOUlZaXmJ maoqOkpaanqKmqsrO0tb a3uLm6wsPExcbHyMnK 0tPU1dbX2Nna4uPk5ebn 6Onq8vP09fb3+Pn6/9oA DAMBAAIRAxEAPwD mYpMe3Q0UUVxn6sj/2 Q==

Binary Data

0101010 0011011 1101100 1000110 0001011 1100100 1000000 1101001 0111001 1001000 0001110 1110110 1111011 1001001

0010111100111001011 0101000101111001101 0001000001010000010 1010001010100110110 1011010110100100101 0010100100110011101 0000010100001001000 0010101000101000001 0100000101000001010 1000101000001010000 1001000001010000010 1000100001011110011 0010011101110100001 0010001000100000101 37

UpTVFVWV1hZWm NkZWZnaGlqc3R1dn d4eXqDhIWGh4iJipK TlJWWl5iZmqKjpK Wmp6ipqrKztLW2t7i 5usLDxMXGx8jJytL T1NXW19jZ2uHi4+T l5ufo6erx8vP09fb3+P n6/8QAHwEAAwEB AQEBAQEBAQAAA AAAAAECAwQFBg cICQoL/8QAtREAAg ECBAQDBAcFBAQ AAQJ3AAECAxEEB SExBhJBUQdhcRMi MoEIFEKRobHBCS MzUvAVYnLRChYk NOEl8RcYGRomJyg pKjU2Nzg5OkNERU ZHSElKU1RVVldY WVpjZGVmZ2hpanN 0dXZ3eHl6goOEhYa HiImKkpOUlZaXmJ maoqOkpaanqKmqsr O0tba3uLm6wsPExcb HyMnK0tPU1dbX2N na4uPk5ebn6Onq8vP 09fb3+Pn6/9oADAM BAAIRAxEAPwDm YpMe3Q0UUVxn6sj/ VG9kYXkgaXMgd29 ya2VycyBkYXk= 001011110011100 101101010001011 110011010001000 001010000010101 000101010011011 010110101101001 001010010100100 110011101000001 010000100100000 101010001010000 010100000101000 001010100010100 000101000010010 000010100000101

1010110 1100101 0111001 0011100 1100100 0000110 0100011 0000101 111001

0000010110111101001 0000100001001110111 0110011101001000010 0001001100111011011 1101001001010000110 1000001011001110100 1100010000110110011 1011011110100110001 000100011010000110 011101010001010001 000110011100110000 010011100100010001 101000001100000101 011001000110011010 000100010101011001 010010010111100000 111000011011000100 101001000011010010 010110011001001001 011010010100010101 101101010010110111 101001100011011101 100100101001101001 011010110011000001 001011010100110100 010101101001010011 010100010101000101 011110000100111001 000100011010110011 011101010000011010 100011010000101011 010010100101001100 110101010001010101 001101010101010011 010011100001010011 010001000110001100 111001010100000110 101001110110001011 110011001001110111 010000100100010001 000001010100010110 111101001100010000 110111011100110100 010011100100010001 101000011101110101 000101000101010000 38

000100001011110 011001001110111 010000100100010 001000001010000 010110111101001 000010000100111 011101100111010 010000100001001 100111011011110 100100101000011 010000010110011 101001100010000 110110011101101 111010011000100 010001101000011 001110101000101 000100011001110 011000001001110 010001000110100 000110000010101 100100011001101 000010001010101 100101001001011 110000011100001 101100010010100 100001101001001 011001100100100 101101001010001 010110110101001 011011110100110 001101110110010 010100110100101 101011001100000 100101101010011 010001010110100 101001101010001 010100010101111 000010011100100 010001101011001 101110101000001 101010001101000 010101101001010 010100110011010 101000101010100 110101010101001 101001110000101

100111011100110111 010010110100001101 001001011011110100 111101111010011100 110011011101001111 011110100111001100 110111010011110111 101001110011001101 110100111101111010 011100110011011101 001111011110100111 001100110111010011 11011110100111001 10011011101001111 01111010011100110 01101110100111101 11101001110011001 10111010011110111 10100111001100110 11101001111011110 10011100110011011 10100111101111010 01110011001101110 10011110111101001 11001100110111010 01111011110100111 00110011011101001 11101111010011100 11001101110100111 10111101001110011 00110111010011110 11110100111001100 11011101001111011 11010011101100010 11110111011101000 00101000001010100 10010000110100000 10100000101001001 01000001010000010 11001110100010001 00000101010011010 01001010000010100 00010110100001000 10101000010010000 01011110000100010 10100001000101111 39

001101000100011 000110011100101 010000011010100 111011000101111 001100100111011 101000010010001 000100000101010 001011011110100 110001000011011 101110011010001 001110010001000 110100001110111 010100010100010 101000010011101 110011011101001 011010000110100 100101101111010 011110111101001 110011001101110 100111101111010 011100110011011 101001111011110 100111001100110 111010011110111 101001110011001 101110100111101 111010011100110 011011101001111 011110100111001 100110111010011 110111101001110 011001101110100 111101111010011 100110011011101 001111011110100 111001100110111 010011110111101 001110011001101 110100111101111 010011100110011 011101001111011 110100111001100 110111010011110 111101001110011 001101110100111 101111010011100

00111000010100010 10000010100100001 11011101000001010 00001010000010101 00010101010101000 01001000001010100 01010001010100001 00100000101010001 01000101010000010 10000010100000101 00000101000001010 00001010000010100 00010100000101000 00101000001010001 01010000110100000 10111011101010001 01000110010000100 11001110110001101 00100101000011010 10001011011110100 11000010111100111 00001010001010000 01011101000101001 00100000101000001 01000001011001110 10001010100010001 00000101110111010 01001010001010100 00010111011101010 10101000110010000 10010000010101000 10100000101000001 01000001010001100 01110010100000101 01000101001001010 00100010000010100 00010101000101010 01001000010010100 10010010010110100 00100110101010101 01000101010001110 10001010011000101 00011001101000010 00010011110010100 10100111100001000 11001000100010010 40

110011011101001 111011110100111 001100110111010 011110111101001 110011001101110 100111101111010 011101100010111 101110111010000 010100000101010 010010000110100 000101000001010 010010100000101 000001011001110 100010001000001 010100110100100 101000001010000 010110100001000 101010000100100 000101111000010 001010100001000 101111001110000 101000101000001 010010000111011 101000001010000 010100000101010 001010101010100 001001000001010 100010100010101 000010010000010 101000101000101 010000010100000 101000001010000 010100000101000 001010000010100 000101000001010 000010100000101 000101010000110 100000101110111 010100010100011 001000010011001 110110001101001 001010000110101 000101101111010 011000010111100 111000010100010 100000101110100

11010000100110101 10110000101000101 01001001010010010 01100000100101101 11100001110111010 10010010101100101 00110011000001100 11001000001011010 11010011010011001 00100101001111001 01100111011001110 11010110100101101 00011001101000011 00011010110010100 01110101001001101 11101101100010010 10011010010110001 10110111101001011 01010011011011110 01100000100111001 01010001011001001 10011010011110100 01000110101100110 11001010001001100 00010100100100011 00101001001101011 01100100010010010 10100110101010101 11000001010100010 10110010001100101 01100101011101010 11000110001011010 00010110100101011 10110110101001110 01101011010110100 10101110101101001 10111001100001010 00111011011000111 00010110001100110 01101010010001100 01011001000110111 00110010000110100 01100101010110000 11100010100010001 10100001001001010 10111010001110110 41

010100100100000 101000001010000 010110011101000 101010001000100 000101110111010 010010100010101 000001011101110 101010101000110 010000100100000 101010001010000 010100000101000 001010001100011 100101000001010 100010100100101 000100010000010 100000101010001 010100100100001 001010010010010 010110100001001 101010101010100 010101000111010 001010011000101 000110011010000 100001001111001 010010100111100 001000110010001 000100101101000 010011010110110 000101000101010 010010100100100 110000010010110 111100001110111 010100100101011 001010011001100 000110011001000 001011010110100 110100110010010 010100111100101 100111011001110 110101101001011 010001100110100 001100011010110 010100011101010 010011011110110 110001001010011 010010110001101

10000011010001101 00101001010011010 01011100000100101 10101010001101100 01001010010101110 10101110110110000 11010101101001010 11010011011010111 00010100101101101 01001110000010010 11010101110110110 10111000000110110 01101001011100000 11100010111001001 00101101111010011 10100010011000101 01110011001001110 10000110111011010 01001101010111010 10111001101001100 01000100011110000 10011010101100001 00011101111000001 11000011010100100 10100111100101110 10001001100010101 00001100010100111 00101100001010111 00110001001110010 11010100101101000 11001001110101010 01000011010010011 01000010101101010 10001101100001101 01011101010110011 00110111100110110 01100101011100100 11110000011100001 11011001010000001 10000001110010110 01100110001000110 01100101011010100 00011011100011011 00010111100111000 01010001010000010 10010000111011101 42

101111010010110 101001101101111 001100000100111 001010100010110 010011001101001 111010001000110 101100110110010 100010011000001 010010010001100 101001001101011 011001000100100 101010011010101 010111000001010 100010101100100 011001010110010 101110101011000 110001011010000 101101001010111 011011010100111 001101011010110 100101011101011 010011011100110 000101000111011 011000111000101 100011001100110 101001000110001 011001000110111 001100100001101 000110010101011 000011100010100 010001101000010 010010101011101 000111011010000 011010001101001 010010100110100 101110000010010 110101010001101 100010010100101 011101010111011 011000011010101 101001010110100 110110101110001 010010110110101 001110000010010 110101011101101 101011100000011

00010101000001010 00001011101110100 01010100001001000 00101010001010001 01010000100100000 10101000101000101 01000010010000010 10100010100000101 00000101000001010 00001010000010100 00010100000101000 00101000101010000 11010000010111011 10101000101000110 01000010011001110 11000110100100101 00001101010001011 01111010011000010 11110011100001010 00101000001011101 00010100100100010 10100000101000001 01100111010001010 10000110100001001 00000101010001010 00100010000100100 00010110001101000 11001000010010000 01010100010100000 10100000101010001 01001010001100110 10000010100000101 00010101000011010 00001011110000100 01010100010101000 01001010011010001 01011110000100001 00110100001001010 01000010010101010 10100010110010001 10100001100011010 10010010011010110 10010100110101101 11101000101010010 01010001100100010 10100101101010010 43

011001101001011 100000111000101 110010010010110 111101001110100 010011000101011 100110010011101 000011011101101 001001101010111 010101110011010 011000100010001 111000010011010 101100001000111 011110000011100 001101010010010 100111100101110 100010011000101 010000110001010 011100101100001 010111001100010 011100101101010 010110100011001 001110101010010 000110100100110 100001010110101 010001101100001 101010111010101 100110011011110 011011001100101 011100100111100 000111000011101 100101000000110 000001110010110 011001100010001 100110010101101 010000011011100 011011000101111 001110000101000 101000001010010 000111011101000 101010000010100 000101110111010 001010100001001 000001010100010 100010101000010 010000010101000 101000101010000

01101111011000100 10010000100001001 00001101010011010 01101011110100101 01010111011001000 00101010110010110 01011011100100110 00101001001000011 01101000010110010 11010110100111001 00111101000101011 01100001110000101 00100110001101011 00101000111010100 10011011110110110 10100101001111001 01100111011100000 10010110110101001 01010100110010010 01110011110100110 01110011010101001 11101101011010011 10010001010101001 00101010101011010 01001000010100110 10001010110110001 00101101010101001 10001010100100101 01100101011001101 10001100100010110 01010101110101011 00111000001101010 0101101001000111 0101011001101101 0101101000110010 0110100001110000 0110000101101110 0100111000110000 0110010001011000 0101101000110011 0110010101001000 0110110000110110 0110011101101111 0100111101000101 0110100001011001 0110000101001000 44

100100000101010 001010000010100 000101000001010 000010100000101 000001010000010 100000101000101 010000110100000 101110111010100 010100011001000 010011001110110 001101001001010 000110101000101 101111010011000 010111100111000 010100010100000 101110100010100 100100010101000 001010000010110 011101000101010 000110100001001 000001010100010 100010001000010 010000010110001 101000110010000 100100000101010 001010000010100 000101010001010 010100011001101 000001010000010 100010101000011 010000010111100 001000101010001 010100001001010 011010001010111 100001000010011 010000100101001 000010010101010 101000101100100 011010000110001 101010010010011 010110100101001 101011011110100 010101001001010 001100100010101 001011010100100 110111101100010

0110100101001001 0110110101001011 0110101101110000 0100111101010101 0110110001011010 0110000101011000 0110110101001010 0110110101100001 0110111101110001 0100111101101011 0111000001100001 0110000101101110 0111000101001011 0110110101110001 0111001101110010 0100111100110000 0111010001100010 0110000100110011 0111010101001100 0110110100110110 0111011101110011 0101000001000101 0111100001100011 0110001001001000 0111100101001101 0110111001001011 0011000001110100 0101000001010101 0011000101100100 0110001001011000 0011001001001110 0110111001100001 0011010001110101 0101000001101011 0011010101100101 0110001001101110 0011011001001111 0110111001110001 0011100001110110 0101000000110000 0011100101100110 0110001000110011 0010101101010000 0110111000110110 0010111100111001 0110111101000001 45

010010000100001 001000011010100 110100110101111 010010101010111 011001000001010 101100101100101 101110010011000 101001001000011 011010000101100 101101011010011 100100111101000 101011011000011 100001010010011 000110101100101 000111010100100 110111101101101 010010100111100 101100111011100 000100101101101 010010101010011 001001001110011 110100110011100 110101010011110 110101101001110 010001010101001 001010101010110 100100100001010 011010001010110 110001001011010 101010011000101 010010010101100 101011001101100 011001000101100 101010111010101 100111000001101 010010110100100 011101010110011 011010101101000 110010011010000 111000001100001 011011100100111 000110000011001 000101100001011 010001100110110 010101001000011 011000011011001

0100010001000001 0100110101000010 0100000101000001 0100100101010010 0100000101111000 0100010101000001 0101000001110111 0100010001101101 0101100101110000 0100110101100101 0011001101010001 0011000001010101 0101010101010110 0111100001101110 0011011001110011 0110101000101111 0011001001010001 0011110100111101

46

100111011011110 100111101000101 011010000101100 101100001010010 000110100101001 001011011010100 101101101011011 100000100111101 010101011011000 101101001100001 010110000110110 101001010011011 010110000101101 111011100010100 111101101011011 100000110000101 100001011011100 111000101001011 011011010111000 101110011011100 100100111100110 000011101000110 001001100001001 100110111010101 001100011011010 011011001110111 011100110101000 001000101011110 000110001101100 010010010000111 100101001101011 011100100101100 110000011101000 101000001010101 001100010110010 001100010010110 000011001001001 110011011100110 000100110100011 101010101000001 101011001101010 110010101100010 011011100011011 001001111011011 100111000100111 000011101100101

000000110000001 110010110011001 100010001100110 010101101010000 011011100011011 000101111001110 010110111101000 001010001000100 000101001101010 000100100000101 000001010010010 101001001000001 011110000100010 101000001010100 000111011101000 100011011010101 100101110000010 011010110010100 110011010100010 011000001010101 010101010101011 001111000011011 100011011001110 011011010100010 111101010110010 001110011100101 101011010110010 101100001101011 011001110110000 101011000010011 010110011101100 100001100100011 100101111001011 000010011001001 010110011110010 110001101111001 010000100110101 101011001010110 000110101100111 10100001010 Table 2: Data Collected after Testing of Project

After collecting this data the encoding step is done. The stego image is created. Then we 47

have to perform some reverse and bit replacement process to get back the base64 format of the original message. If we get that data we can obtain the original text from that. Thus the whole encoding and decoding processes are done in our project “An android application for image steganography”.

Figure 18: App icon

48

CHAPTER 6 CONCLUSION ‘Image Steganography' allows us to embed text and files into images, with optional encryption. Here we are using the term image steganography for hiding message data in image data bits. Here for image steganography process in our project android app we are using new techniques. We can input cover image of small size. Thus execution of encoding and decoding will take less time. Images with size of less than 10 pixels will be better. Users will experience the app with more reliability. We shall try to build this app as a very efficient app and installable in most of the versions of android. Our project app is built in android platform and designed by android studio. In operating system windows 10 we have developed this app. In previous chapters - chapter 3, chapter 4, chapter 5 we have discussed the app’s efficiency, designing methods, used algorithms and some collected results obtained after testing the app.

49

REFERENCES [1] Feng, J.B., Lin, I.C., Tsai, C.S., Chu, Y.P., 2006. Reversible watermarking: current status and key issues. International Journal of Network Security 2 (May), 161–170. [2] C. K. Chan, L. M. Cheng, “Hiding data in image by simple LSB substitution”, pattern recognition, Vol. 37, No. 3, 2004, pp. 469-474. [3] R. Chandramouli, N. Memon, “Analysis of LSB Based Image Steganography Tech-niques”, IEEE pp. 1019-1022,2001. [4] Jhukkj F. Hartung and M. Kutte "Information hiding-a survey, " Proceedings of the IEEE: Special Issue on Identification and Protection of Multimedia Content, Volume: 87 Issue:7, pp. I062-I078, July. 1999. [5] Nidhi Sharma, Manu Devi, “Improved Detection of Least Significant Bit Steganography Algorithms in Color and Gray Scale Images,” Proceedings of 2014 RAECS UIET Panjab University Chandigarh,06-08, March 2014. [6] Padmini.K, Champakamala .B.S, Radhika .D. K Asst Professors, Department of TCE, Don Bosco Inst-itute of Technology, Bangalore, “Least Significant Bit algorithm for image steganography”India International Journal of Advanced Computer Technology(IJACT), Volume 3,Number 4. [7] Kaur Jaspreet and Singh Sandeep “Odd-Even Mes-sage Bit Sequence Based Image Steganography”, (IJC SIT) International Journal of Computer Science and Information Technologies, Vol. 6 (4) , 2015, 3930-3932 . [8] S.Ibrahim,M.R.K. atmin, M.M.Amin,M.Salleh, and M.Z.I. Shamsuddin “Information Hiding using Steganography” 4* National Conference on Telecom-munication. Technology Proceedings, Shah Alam, Malaysia.2003 IEEE [9] Wang, H & Wang, S, “Cyber warfare: Steganography vs. Steganalysis”, Communications of the ACM, 47:10, October 2004 50

[10] Morkel T., Eloff J. H. P., and Olivier M. S., “An Overview of Image Steganography”, Information and Computer Security Architecture (ICSA) Research Group, University of Pretoria, South Africa, 2005.. [11] E. L. Hall. Computer Image Processing and Recognition. New York: Academic Press, 1979. [12] J. Burns. Developing Secure Mobile Application. ISEC Parnters, October 2008. https://www.isecpartners.com/files/iSEC_Securing_Android_Apps.pdf, accessed November 2010. [13] Wikipedia. Android.Wikipedia, 2010.http://en.wikipedia.org/wiki/ Android(operating system), accessed October 2010.

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APPENDIX In appendix I have added ‘Plagiarism Report’ at the end of my report and attached one CD with report which contains A-Z all digital data of whole dissertation.

52