video encryption mini project content

7/27/2019 Video encryption Mini project Content

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1. INTRODUCTION

1.1 INTRODUCTION

The rapid growth of Internet and digitized content has made video distribution easy. Hence

the need for video data protection is on the rise. Therefore, multimedia encryption is needed for the

complete confidentiality. Classic encryption algorithms like DES (Data Encryption Standard), AES

(Advanced Encryption Standard) etc., are computationally infeasible for video data. They take

large amount of time for encrypting huge video data. To decrease the encryption time, some

encryption algorithms used simple scrambling mechanisms. Evidently they are insecure. Moreover,

these algorithms typically neglected the data format of the videos, thus burdening compression

phase of codec.

Owing to the large size and real-time applications of video, two types of encryption

algorithms are generally in vogue. One method is selective encryption. In this method, only parts of

the video content are encrypted, thereby reducing the computational requirement (time). This

method is not suitable because the full content of the video is not critical. Another method is the

light-weight encryption which trades off security for computational time.

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1.2 OBJECTIVE

The objective is to propose a secure and computationally feasible video encryption

algorithm based on the method of Secret Sharing. In an MPEG video, the strength of the DC is

distributed among the AC values based on Shamirs Secret Sharing (SSS) scheme. The proposed

algorithm guarantees security, speed and error tolerance with a small increase in video size. There

is a need for a new secure video encryption algorithm perhaps designed by combining these two

classes, which retains their respective advantages, while minimizing the disadvantages. Apparently

a naive combination is worse compared to each one of them individually if one wants to reduce

the time, then one may opt for selective light-weight encryption, which degrades the security. If

one attempts to improve security by the Shannons principle of selective permute-then-encrypt, it

increases the computational time.

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2. SYSTEM ANALYSIS

2.1 EXISTING SYSTEM

In the existing system, the selective encryption algorithm typically uses heavy-weight

encryption algorithms (eg. DES, AES etc.). Consequently, time taken for the encryption using them

is high making them unsuitable for real-time applications. On the other hand, most of the known

light-weight algorithms are susceptible to known plaintext-only and ciphertext-only attacks.

Therefore, there is a need for a new secure video encryption algorithm perhaps designed by

combining these two classes, which retains their respective advantages, while minimizing the

disadvantages. Apparently a naive combination is worse compared to each one of them

individually if one wants to reduce the time, then one may opt for selective light-weight

encryption, which degrades the security. If one attempts to improve security by the Shannons

principle of selective permute-then-encrypt, it increases the computational time.

2.1.1 LIMITATIONS

The existing video encryption techniques are not feasible.

The security is very low.

Cannot overcome the secret sharing attacks

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2.2 PROPOSED SYSTEM

In the proposed system, we propose a selective cum light-weight encryption algorithm

which is fast enough for real-time applications, yet possessing practically acceptable levels of

security. Discrete Cosine Tranform (DCT) is popularly used to compress images and videos. It

decomposes an image signal into multiple frequency components. A key ingredient of our solution

is a suitably adapted and randomized version of Shamirs Secret Sharing scheme. Furthermore, our

algorithm, unlike most of the video encryption algorithms, has an inbuilt error-tolerance, which

could be handy in many practical applications.

2.2.1 ADVANTAGES

Provides a low cost solution to Encryption and provides good quality video encoding.

Provides overall high security, size preservation, and relatively fast encryption.

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3. SYSTEM SPECIFICATION

3.1 HARDWARE REQUIREMENTS

Processor : Pentium IV

Speed : Above 500 MHz

RAM capacity : 1 GB

Hard disk drive : 80 GB

Motherboard : Intel

3.2 SOFTWARE REQUIREMENTS

Operating System : Windows XP and above

Technology : MATLAB

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4. SOFTWARE DESCRIPTION

4.1 MATLAB

MATLAB is a high-level technical computing language and interactive environment for

algorithm development, data visualization, data analysis, and numeric computation. Using the

MATLAB product, one can solve technical computing problems faster than with traditional

programming languages, such as C, C++, and Fortran.

One can use MATLAB in a wide range of applications, including signal and image

processing, communications, control design, test and measurement, financial modeling and

analysis, and computational biology. Add-on toolboxes extend the MATLAB environment to solve

particular classes of problems in these application areas.

MATLAB provides a number of features for documenting and sharing the work. One can

integrate the MATLAB code with other languages and applications, and distribute the MATLAB

algorithms and applications.

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4.2 KEY FEATURES

High-level language for technical computing

Development environment for managing code, files, and data

Interactive tools for iterative exploration, design, and problem solving

Mathematical functions for linear algebra, statistics, Fourier analysis, filtering,

optimization, and numerical integration

2-D and 3-D graphics functions for visualizing data

Tools for building custom graphical user interfaces

Functions for integrating MATLAB based algorithms with external applications and

languages, such as C, C++, Fortran, Java, COM, and Microsoft Excel

Image Processing Toolbox 6.3

Performs image processing, analysis, and algorithm development

Image Processing Toolbox software provides a comprehensive set of reference-standard algorithms

and graphical tools for image processing, analysis, visualization, and algorithm development. One

can restore noisy or degraded images, enhance images for improved intelligibility, extract features,

analyze shapes and textures, and register two images. Most toolbox functions are written in the

open MATLAB language, giving one the ability to inspect the algorithms, modify the source code,

and create own custom functions.

Introduction

Image Processing Toolbox supports engineers and scientists in areas such as biometrics,

remote sensing, surveillance, gene expression, microscopy, semiconductor testing, image sensor

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design, color science, and materials science. It also facilitates the learning and teaching of image

processing techniques.

Key Features

Image enhancement, including filtering, filter design, deblurring, and contrast enhancement

Image analysis, including feature detection, morphology, segmentation, and measurement

Spatial transformations and image registration

Image transforms, including FFT, DCT, Radon, and fan-beam projection

Support for multidimensional image processing

Support for ICC version 4 color management system

Modular interactive tools, including ROI selections, histograms, and distance measurements

Interactive image and video display

DICOM import and export

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5. PROJECT DESCRIPTION

5.1 PROBLEM DEFINITION

The rapid growth of Internet and digitized content has made video distribution easy. Hence

the need for video data protection is on the rise. A secure and computationally feasible video

encryption algorithm based on the method of Secret Sharing is proposed for use. In an MPEG

video, the strength of the DC is distributed among the AC values based on Shamirs Secret Sharing

(SSS) scheme. The proposed algorithm guarantees security, speed and error tolerance with a small

increase in video size.

5.2 OVERVIEW OF THE PROJECT

The overview of the project is to propose a secure and computationally feasible video

encryption algorithm based on the method of Secret Sharing. In an MPEG video, the strength of the

DC is distributed among the AC values based on Shamirs Secret Sharing (SSS) scheme. The

proposed algorithm guarantees security, speed and error tolerance with a small increase in video

size. There is a need for a new secure video encryption algorithm perhaps designed by combining

these two classes, which retains their respective advantages, while minimizing the disadvantages.

We propose a selective cum light-weight encryption algorithm which is fast enough for real-time

applications, yet possessing practically acceptable levels of security. Discrete Cosine Tranform

(DCT) is popularly used to compress images and videos. It decomposes an image signal into

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multiple frequency components. A key ingredient of our solution is a suitably adapted and

randomized version of Shamirs Secret Sharing scheme.

5.3 MODULE DESCRIPTION

The project has the following module implementations

1. Implementation of Discrete Cosine Transform (DCT) to compress the Video

2. Encryption and Secret Sharing by Shamirs secret sharing scheme

3. Decryption Process

4. Compute Error Tolerance

5. Performance Evaluation

5.3.1 MODULES

1. Implementation of Discrete Cosine Transform (DCT) to compress the Video

In this module, we implement the Discrete Cosine Transform (DCT) to compress images

and videos. It decomposes an image signal into multiple frequency components. The transform

coefficients can be classified into two groups namely, DC and AC coefficients. The DC coefficient

is the mean value of the image block and carries most of the energy in the image block. The AC

coefficients (ACs) carry energy depending on the amount of detail in the image block. In practice,

most of the energy is compacted in the DC coefficient and a few AC coefficients.

2. Encryption and Secret Sharing by Shamirs secret sharing scheme

In this module, Shamirs (k, n) secret sharing scheme is used, where n = k + 1. The value of

k varies from 4 to 12 depending on the number of ACs in that block. Though the DC can be shared

among all the ACs available, it has the drawback of increase in video size as well as the decryption

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time at the receiver. This algorithm is a selective and light-weight encryption algorithm. It takes the

DC component of each DCT block. Depending on the number of ACs in that block it distributes

the DC among the ACs and itself, based on the method of secret sharing.

3. Decryption Process

In this module, during decryption at the receiver end, the authorized user first has to

generate a set of random numbers using the key (seed) as the input to PRNG and then proceed with

constructing k equations from n values. Then use LaGranges interpolation to get back the DC and

AC coefficients of each block. Even if receiver loses nk values (only one value in the current

setting), he can retrieve all the DCT coefficients correctly. An unauthorized user cannot get back

the secret because of the property that any k 1 shares doesnt reveal anything about the secret.

3. Compute Error Tolerance

In this module, the Secret Sharing is the key factor that helps in providing error tolerance.

In the proposed algorithm, k values are distributed among k + 1 values. So, loss or change of one

value can be tolerated. This feature of the algorithm comes with extra computational overhead

which is also tolerable. If a value is lost, rest of the k values can be used to get back the original

coefficients according to secret sharing. If a value is modified, the original values can be obtained

by trial-and-error in at most k 1 iterations. Hence error-tolerance is achieved.

4. Performance Analysis

In this module, the proposed algorithm is evaluated for the following:

Security of the proposed encryption technique and

The process of achieving error tolerance.

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5.4 DATA FLOW DIAGRAM

LEVEL 0

Figure 1. DFD level 0

12

User

A novel video

encryption

technique basedon secret

sharing

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LEVEL 1

Figure 2. DFD level 1

13

Video

User

Compress the

video by DCT

Encryption andSecret Sharing by

Shamirs secretsharing scheme

Compute Error

Tolerance

Decryption

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5.5 INPUT DESIGN

Input design is the part of overall system design which requires very careful attention. Often

the collection of input data is the most expensive part of the system, in terms of both the equipment

used and the number of people involved; it is the point of most contact for the users with the

computer system; and it is prone to error. If data going into the system are incorrect, then the

processing and output will magnify these errors.

Input design is the very important part in the project and should be concentrated well as it is

prone to error. The data that are to be inserted are to be inserted with care as this plays a very

important role. In order to get the meaningful output and to achieve good accuracy the input should

be acceptable and understandable by the user.

There are various approaches for entering data through terminals. This project is implemented as a

MATLAB application. The essential things that are considered during input design are:

The content of the input records: Data items from the inputs will be used to produce the

output.

Design of the source document: Source data is usually recorded in order to standardize

the format of input data. Properly designed source documents also aid accuracy and

checking procedures.

User interface design: User input is usually through keyboard and mouse.

Volume and frequency of input: This will dictate the method of input. Usually small

volumes of data are input using VDU and thus here too it is input using VDU, validated and

processed immediately.

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5.6 OUTPUT DESIGN

Output design plays a very important role in a system. Getting a correct output is a task that

has to be concentrated, as a system is validated as a correct one only if it gives the correct output

according to the input.

Computer output is the most important and direct source of information to the user.

Efficient and intelligent output design should improve the systems relationship with the user and

helps in decision making. The output devices depend on factors such as compatibility of the device

with the system, response time, requirements and so on.

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6. SYSTEM TESTING

6.1 UNIT TESTING

Unit testing is the testing of individual hardware or software units or groups of related unit.

Using white box testing techniques, testers verify that the code does what it is intended to do at a

very low structural level. For example, the tester will write some test code that will call a method

with certain parameters and will ensure that the return value of this method is as expected. Looking

at the code itself, the tester might notice that there is a branch (an if-then) and might write a second

test case to go down the path not executed by the first test case. When available, the tester will

examine the low-level design of the code; otherwise, the tester will examine the structure of the

code by looking at the code itself. Unit testing is generally done within a class or a component.

6.2 ACCEPTANCE TESTING

After functional and system testing, the product is delivered to a customer and the customer

runs black box acceptance tests based on their expectations of the functionality. Acceptance testing

is formal testing conducted to determine whether or not a system satisfies its acceptance criteria

(the criteria the system must satisfy to be accepted by a customer) and to enable the customer to

determine whether or not to accept the system. These tests are often pre-specified by the customer

and given to the test team to run before attempting to deliver the product. The customer reserves

the right to refuse delivery of the software if the acceptance test cases do not pass. However,

customers are not trained software testers. Customers generally do not specify a complete set of

acceptance test cases. Their test cases are no substitute for creating our own set of

functional/system test cases. The customer is probably very good at specifying at most one good

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test case for each requirement. Whenever possible, we should run customer acceptance test cases

ourselves so that we can increase our confidence that they will work at the customer location.

PROGRAM TESTING

A program represents the logical elements of a system. For a program to run

satisfactorily, it must compile and test data correctly and tie in properly with other

programs. Achieving an error free program is the responsibility of the programmer. Program

testing checks for two types of errors: syntax and logical. Syntax error is a program

statement that violates one or more rules of the language in which it is written. An

improperly defined field dimension or omitted keywords are common syntax errors. These errors

are shown through error message generated by the computer. For Logic errors the programmer

must examine the output carefully.

When a program is tested, the actual output is compared with the expected output.

When there is a discrepancy the sequence of instructions must be traced to determine the

problem. The process is facilitated by breaking the program into self-contained portions,

each of which can be checked at certain key points .The idea is to compare program

values against desk-calculated values to isolate the problems.

FUNCTIONAL TESTING

Functional testing of an application is used to prove the application delivers correct results,

using enough inputs to give an adequate level of confidence that will work correctly for all sets of

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inputs. The functional testing will need to prove that the application works for each client type and

that personalization function work correctly.

Test case no Description Expected result

1 Test for all modules All module should

communicate in the

application.

2 Test for every functions in a framework

as it display all results.

The result after execution

should give the accurate

result.NON-FUNCTIONAL TESTING

This testing is used to check that an application will work in the operational environment.

Non-functional testing includes:

Load testing

Performance testing

Usability testing

Reliability testing

LOAD TESTING


1 It is necessary to ascertain that the

application behaves correctly under

loads of all the components.

Should display error

message for particular

components.

PERFORMANCE TESTING

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1 This is required to assure that an

application perforce adequately, having

the capability to handle many peers,

delivering its results in expected time

and using an acceptable level of resource

and it is an aspect of operational

management.

Should handle large input

values, and produce

accurate result in a

expected time

RELIABILITY TESTING


1 This is to check that the system is rugged

and reliable and can handle the failure of

any of the components involved in

provide the application.

In case of failure of the

system an error handling

function should take over

the process

7. SYSTEM IMPLEMENTATION

System implementation is the important stage of project when the theoretical design is tuned

into practical system. The main stages in the implementation are as follows:

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Planning

System testing and

Changeover Planning

Planning is the first task in the system implementation. Planning means deciding on the

method and the time scale to be adopted. At the time of implementation of any system people from

different departments and system analysis involve. They are confirmed to practical problem of

controlling various activities of people outside their own data processing departments. The line

managers are controlled through an implementation coordinating committee. The committee

considers ideas, problems and complaints of user department, it must also consider:

The implication of system environment;

Self selection and allocation for implementation tasks;

Consultation with unions and resources available;

Standby facilities and channels of communication

RESULTS

Since the Office Management is a system, which is to be accessed, only by the company

management alone only one user should design it, in such a way that it should not be flexible

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enough to access at a time. Hence the implementation method used in the system is a pilot type of

implementation.

IMPLEMENTATION PROCEDURES

The implementation plan consists of the methods for changing from the old system to new

one. There are several methods available for handling the implementation and consequent

conversion from old to the new computerization system. The most secure method for converting

from the old to the new system is to run both old and new systems in parallel. In this approach

personal may operate in the manual order processing system in the accustomed manner as well as

start operating the new computerization system. This method offers high security, because even if

there is a flaw in the computerization system we can depend on the manual system. However, the

cost for maintaining two systems in parallel is very high.

Another commonly used method is a direct cutter from the existing system to the proposed

system. The change may be within a week or within a day. There are no parallel activities.

However, there is no remedy in case of a problem. This strategy requires careful planning.

We can also implement a working version of the system in one part of the organization and

the personal will be piloting the system and changes can be made as and when required. But this

method is less preferable due to the loss of entire system.

OPERATIONAL DOCUMENTATION

An Operational Manual is used as a permanent reference document to inform the computer

operations department to implement the work to be done in routine operation and any special

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features. The manual is the formal communication of system details to the operations department,

but is not the only communication needed. It is essential that provisional details be supplied to the

operations department as soon as they are available to give opportunity for preparation of

preliminary schedules and forward loading plans and for training and familiarization. The contents

should be clear and practical. As it may be necessary for the manual to be partitioned to the

requirements, its structure should be determined in consultation with the operations developer.

IMPLEMENTATION STEP

The Discrete Cosine Transform (DCT) is implemented to compress images and videos. It

decomposes an image signal into multiple frequency components. The transform

coefficients can be classified into two groups namely, DC and AC coefficients. The DC

coefficient is the mean value of the image block and carries most of the energy in the image

block. The AC coefficients (ACs) carry energy depending on the amount of detail in the

image block. In practice, most of the energy is compacted in the DC coefficient and a few

AC coefficients.

Shamirs (k, n) secret sharing scheme is used, where n = k + 1. The value of k varies from 4

to 12 depending on the number of ACs in that block. Though the DC is shared among all

the ACs available, it has the drawback of increase in video size as well as the decryption

time at the receiver. This algorithm is a selective and light-weight encryption algorithm. It

takes the DC component of each DCT block. Depending on the number of ACs in that

block distributes the DC among the ACs and itself, based on the method of secret sharing.

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During decryption at the receiver end, the authorized user first has to generate a set of

random numbers using the key (seed) as the input to PRNG and then proceed with

constructing k equations from n values then use Legranges interpolation to get back the

DC and AC coefficients of each block. Even if receiver loses nk values (only one value in

the current setting), he can retrieve all the DCT coefficients correctly. An unauthorized user

cannot get back the secret because of the property that any k 1 shares doesnt reveal

anything about the secret.

The Secret Sharing is the key factor that helps in providing error tolerance. In the proposed

algorithm, k values are distributed among k + 1 values. So, loss or change of one value can

be tolerated. This feature of the algorithm comes with extra computational overhead which

is also tolerable. If a value is lost, rest of the k values can be used to get back the original

coefficients according to secret sharing. If a value is modified, the original values can be

obtained by trial-and-error in at most k 1 iterations. Hence error-tolerance is achieved.

8. CONCLUSION

8.1 CONCLUSION

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In this project, a novel selective and light-weight encryption algorithm for the security of

video data is proposed based on the method of sharing the DC coefficients among the ACs and DC.

Security analysis and experimental results show that the proposed encryption scheme is fast,

provides good security with error tolerance and adds very less overhead on the compression of the

video which most of the real-time video applications require. The Discrete Cosine Transform

(DCT) is implemented to compress images and videos. Then Shamirs (k, n) secret sharing scheme

is used, where n = k + 1. The value of k varies from 4 to 12 depending on the number of ACs in

that block. The proposed algorithm increases the video size by 30.23% which is less when

compared to XOR and scramble algorithms. Though the DC is shared among all the ACs available,

it has the drawback of increase in video size as well as the decryption time at the receiver.

8.2 FUTURE ENHANCEMENT

The future scope is to extend this system to adapt the algorithm for different resolution

videos, different video formats and highly sensitive videos where every part of the video is

important. Furthermore the encryption time can be reduced so that it can be used to support large

video applications.

9. APPENDIX-1

9.1 Source code

Encrypt.m:

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function varargout = final(varargin)

gui_Singleton = 1;

gui_State = struct('gui_Name', mfilename, ...'gui_Singleton', gui_Singleton, ...

'gui_OpeningFcn', @final_OpeningFcn, ...

'gui_OutputFcn', @final_OutputFcn, ...'gui_LayoutFcn', [] , ...

'gui_Callback', []);

if nargin && ischar(varargin{1})gui_State.gui_Callback = str2func(varargin{1});

end

if nargout

[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});else

gui_mainfcn(gui_State, varargin{:});

end

function final_OpeningFcn(hObject, eventdata, handles, varargin)handles.output = hObject;

guidata(hObject, handles);function varargout = final_OutputFcn(hObject, eventdata, handles)

varargout{1} = handles.output;

function popupmenu1_Callback(hObject, eventdata, handles)function popupmenu1_CreateFcn(hObject, eventdata, handles)

if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))

set(hObject,'BackgroundColor','white');

endfunction pushbutton1_Callback(hObject, eventdata, handles)

clc;

warning off all;if(isdir('frames'))

rmdir('frames','s');

endmkdir('frames');

switch get(handles.popupmenu1,'Value')

case 1

case 2im='Input\human.avi';

case 3

im='Input\viptraffic.avi';case 4

im='Input\hockey ground.avi';

case 5im='Input\xylo.avi';

end

xyloObj = mmreader(im)

file=im;

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mov=[];

pickind = 'tif';

pathname = 'frames\';f=xyloObj.Numberofframes;

for k = 1 : f

mov{k} = read(xyloObj, k);strtemp=strcat(pathname,int2str(k),'.',pickind);

imwrite(mov{k},strtemp);

endfigure('name','Input video','numbertitle','off')

for k = 1 : f

imshow(mov{k});

hold onpause(0.05)

end

im=[];

block=[];dct_block=[];

idc=[];[m n p]=size(mov{1});

h=waitbar(0,'Applying DCT');

for t=1:fwaitbar(t/f)

strtemp=strcat(pathname,int2str(t),'.',pickind);

im{t}=imread(strtemp);

c2= mat2cell(im{t}, 10*ones(1, (m/10)), 10*ones(1, (n/10)),3);block{t}=c2;

d=[];id1=[];

for i=1:size(c2,1)for j=1:size(c2,2)

x=c2{i,j};

for p=1:3d1(:,:,p)=dct2(x(:,:,p));

id(:,:,p)=idct2(d1(:,:,p));

end

d{i,j}=d1;id1{i,j}=id;

end

enddct_block{t}=d;

idc{t}=id1;

endclose(h)

disp('Blocks')

disp(block)

disp('DCT-Blocks')

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disp(dct_block)

h1=waitbar(0,'Encrypting the frames');

en_bl=[];r1=rand(1);r2=rand(1);

save po1 r1 r2

r1=rand(1);r2=rand(1);save po2 r1 r2

r1=rand(1);r2=rand(1);

save po3 r1 r2ienk=[];

alk=[];

q=0;q1=0;q2=0;

for t=1:ftic

waitbar(t/f)

d2=dct_block{t};

en=[];ien=[];for i=1:size(c2,1)

for j=1:size(c2,2)d3=d2{i,j};

for p=1:3

d4=d3(:,:,p);dc=d4(1,1);

a=find(d4>0);

if(a(1)==1)

a1=length(a)-1;else

a1=length(a);

endal(i,j)=a1;

if(a15)

z=1;dk=subfun(z,d4,a1);

q=q+1;

elseif(a1>=10 && a120)z=3;

dk=subfun(z,d4,a1);

q2=q2+1;end

ak(:,:,p)=dk;

ek(:,:,p)=idct2(dk);

end

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en{i,j}=ak;

ien{i,j}=ek;

endend

en_bl{t}=en;

ienk{t}=ien;alk{t}=al;

ti(t)=toc;

endclose(h1)

disp('Encrypted Blocks')

disp( en_bl)

if(isdir('en_frames'))rmdir('en_frames','s');

end

mkdir('en_frames');

pathname1 = 'en_frames\';for i=1:f

strtemp1=strcat(pathname1,int2str(i),'.',pickind);enp=en_bl{i};

imwrite(cell2mat(enp),strtemp1);

endname1='encrypted.avi';

aviobj = avifile(name1);

path='en_frames\';

fram2mov('en_frames\*.tif',aviobj,name1,path)save fi1 file

save ti1 ti

save alk1 alksave ftt f

save dcb dct_block

save cc c2save mov1 mov

function pushbutton2_Callback(hObject, eventdata, handles)

load alk1

load fttload dcb

load cc

load mov1pickind = 'tif';

ii=decryp(alk,f,dct_block,c2);

if(isdir('de_frames'))rmdir('de_frames','s');

end

mkdir('de_frames');

pathname2= 'de_frames\';

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for i=1:f

strtemp2=strcat(pathname2,int2str(i),'.',pickind);

imwrite(uint8(ii{i}),strtemp2);end

name2='decrypted.avi';

aviobj1 = avifile(name2);path1='de_frames\';

fram2mov('de_frames\*.tif',aviobj1,name2,path1)

for i=1:fk1=mov{i};

k2=uint8(ii{i});

er(i)=mean(mean(mean((k1-k2))))/100;

endsave er1 er


load fi1

load er1load ti1

fileinfo = aviinfo(file);fileinfo1 = aviinfo('encrypted.avi');

v1=fileinfo.FileSize/1024;

v2=fileinfo1.FileSize/1024;figure('name','Comparison by size','numbertitle','off')

bar(3,v1,'r');

hold on

bar(6,v2,'m');axis([1 10 0 max(v1,v2)+200])

xlabel('Videos')

ylabel('Size (Bytes)')legend('Original','Encrypted')

figure('name','Time For Encryption','numbertitle','off')

plot(1:length(ti),ti,'m');xlabel('Different frames')

ylabel('Time (Sec)')

figure('name','Error For Encryption','numbertitle','off')

plot(1:length(er),er,'r');xlabel('Different frames')

ylabel('Error')


close all;

clc;

subfunction.m:

function dk=subfun(z,d4,a1)

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if(z==1)

dk=d4;

r=4;load po1;

acn=d4(a1);

dk(1)=poly(d4,r1);dk(1,2)=poly(d4,r2);

dk(1,3)=poly(d4,2);

dk(1,4)=poly(d4,3);dk(a1)=poly(d4,a1);

end

if(z==2)

dk=d4;r=8;

load po2;

dk(1)=poly1(d4,r1);

dk(1,2)=poly1(d4,r2);dk(1,3)=poly1(d4,2);

dk(1,4)=poly1(d4,3);dk(1,5)=poly1(d4,4);

dk(1,6)=poly1(d4,5);

dk(1,7)=poly1(d4,6);dk(1,8)=poly1(d4,7);

dk(a1)=poly1(d4,a1);

end

if(z==3)dk=d4;

r=8;

load po3;acn=d4(a1);

dk(1)=poly2(d4,r1);

dk(1,2)=poly2(d4,r2);dk(1,3)=poly2(d4,2);

dk(1,4)=poly2(d4,3);

dk(1,5)=poly2(d4,4);

dk(1,6)=poly2(d4,5);dk(1,7)=poly2(d4,6);

dk(1,8)=poly2(d4,7);

dk(1,9)=poly2(d4,8);dk(1,10)=poly2(d4,9);

dk(2,1)=poly2(d4,10);

dk(2,2)=poly2(d4,11);dk(a1)=poly2(d4,a1);

end

function f=poly(d4,x)

dc=d4(1);

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ac1=d4(1,2);ac2=d4(1,3);ac3=d4(1,4);

f1=ac3*(x^3)+ac2*(x^2)+ac1*(x^1)+dc;

f=mod(f1,251);function f=poly1(d4,x)

dc=d4(1);

ac1=d4(1,2);ac2=d4(1,3);ac3=d4(1,4);ac4=d4(1,5);ac5=d4(1,6);ac6=d4(1,7);ac7=d4(1,8) ;f1=ac7*(x^7)+ac6*(x^6)+ac5*(x^5)+ac4*(x^4)+ac3*(x^3)+ac2*(x^2)+ac1*(x^1)+dc;

f=mod(f1,251);

function f=poly2(d4,x)dc=d4(1);

ac1=d4(1,2);ac2=d4(1,3);ac3=d4(1,4);ac4=d4(1,5);ac5=d4(1,6);ac6=d4(1,7);ac7=d4(1,8);ac8=d4(1

,9);ac9=d4(1,10);ac10=d4(2,1);ac11=d4(2,2);

f1=ac11*(x^11)+ac10*(x^10)+ac9*(x^9)+ac8*(x^8)+ac7*(x^7)+ac6*(x^6)+ac5*(x^5)+ac4*(x^4)

+ac3*(x^3)+ac2*(x^2)+ac1*(x^1)+dc;

f=mod(f1,251);

Frames2movie.m:

function fram2mov(dname,aviobj,name,path)

dirData = dir(dname)% dirData =dir(dname);

fileNames = {dirData.name};

l=length(fileNames);

for i=1:l[a, map] = imread(strcat(strcat(path,int2str(i),'.tif')));

M = im2frame(a);

aviobj = addframe(aviobj,M);end

disp('Closing movie file...')

aviobj = close(aviobj);%play the movie

disp('Playing movie file...')

implay(name);

decrypt.m:

% decryption

function ii=decryp(alk,f,dc,c2)ii=[];

for t=1:f

w=alk{t};

d2=dc{t};

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id1=[];

for i=1:size(c2,1)

for j=1:size(c2,2)w1=w(i,j);

if(w1>30)

x=d2{i,j};for p=1:3

ui(:,:,p)=idct2(x(:,:,p));

endid1{i,j}=ui;

else

id1{i,j}=d2{i,j};

endend

end

ii{t}=cell2mat(id1);

end

10.APPENDIX-2

SCREEN SHOTS

1.Main page

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2.Applying DCT:

Video is given as input to the DCT function.

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3.Encrypting frames

The frames are encrypted using Secret Sharing algorithm.

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4.Encrypted video

The encrypted frames are converted to movie file format.

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5.Encrypted frames:

Images of encrypted frames.

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6.Decrypted video

The encrypted video is decrypted by reverse process of encryption.

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7.Decrypted frames

Images of the decrypted frames.

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8.Comparison by Size

The comparison is made between original video and encrypted video.

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9.Time taken for encryption

Time taken for each frame for encryption is calculated and plotted.

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10.Error for encryption

The difference between original video and decrypted video is calculated.

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11. REFERENCES

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[1] L. Tang, Methods for encrypting and decrypting MPEG video data efficiently, in Proc. of

ACM Multimedia, pp. 219229.

[2] L. Qiao and Klara Nahrstedt, A new algorithm for MPEG video encryption, in Proc. of First

International Conference on Imaging Science System and Technology, 1997, pp. 2129.

[3] Wenjun Zeng and Shawmin Lei, Efficient frequency domain selective scrambling of digital

video, in Proc. of the IEEE Transactions on Multimedia, 2002, pp. 118129.

[4] Zhenyong Chen, Zhang Xiong, and Long Tang, A novel scrambling scheme for digital video

encryption, in Proc. of Pacific-Rim Symposium on Image and Video Technology( PSIVT), 2006,

pp. 9971006.

[5] B. Furht and D. Kirovski, Multimedia Security Handbook, CRC Press LLC, 2004.

[6] C. Shi and Bharat Bhargava, A fast MPEG video encryption algorithm, in Proc. of ACM

Multimedia, 1998, pp. 8188.

[7] A. Shamir, How to share a secret, in Proc. of Communications of the ACM, 1979, vol. II, pp.

612613.

[8] Zheng Liu, Xue Li, and Zhaoyang Dong, Enhancing security of frequency domain video

encryption, in Proc. of ACM Multimedia, 2004, pp. 304307.

[9] J. Meyer and F. Gadegast, Security mechanisms for multimedia data with the example MPEG-

1 video, available at www.gadegast.de/frank/doc/secmeng.pdf.

[10] Wei-Tsang Ooi, Brian Smith, Sugata Mukhopadhyay, Haye Hsi Chan, SteveWeiss,Matthew

Chiu, and Jiesang Song, The DALI multimedia software library, in SPIE Multimedia Computing

and Networking, 1999.

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