novel video encryption

7/27/2019 Novel video encryption

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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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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 design, color

science, and materials science. It also facilitates the learning and teaching of image processing techniques.

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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 multiple frequency components. A key ingredient of our

solution is a suitably adapted and randomized version of Shamirs Secret Sharing scheme.

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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 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.

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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 videoencryption

technique based

on secret

sharing

User


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LEVEL 1

Figure 2. DFD level 1

13

Video

User

Compress the

video by DCT

Encryption and

Secret Sharing by

Shamirs secretsharing scheme

Compute ErrorTolerance

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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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

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most one good 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 inputs. The

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

personalization function work correctly.

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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 enough to

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

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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 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

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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.

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.

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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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Encrypt.m:

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});

endif 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');

end

function pushbutton1_Callback(hObject, eventdata, handles)clc;

warning off all;

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

end

mkdir('frames');

switch get(handles.popupmenu1,'Value')case 1

case 2

im='Input\human.avi';case 3

im='Input\viptraffic.avi';

case 4im='Input\hockey ground.avi';

case 5

im='Input\xylo.avi';

end

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xyloObj = mmreader(im)

file=im;

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);

end

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

for k = 1 : fimshow(mov{k});

hold on

pause(0.05)

endim=[];

block=[];dct_block=[];

idc=[];

[m n p]=size(mov{1});h=waitbar(0,'Applying DCT');

for t=1:f

waitbar(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=1:3

d1(:,:,p)=dct2(x(:,:,p));

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

d{i,j}=d1;

id1{i,j}=id;end

end

dct_block{t}=d;idc{t}=id1;

end

close(h)

disp('Blocks')

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disp(block)

disp('DCT-Blocks')

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 r2r1=rand(1);r2=rand(1);

save po3 r1 r2

ienk=[];

alk=[];q=0;q1=0;q2=0;

for t=1:f

tic

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;

elsea1=length(a);

end

al(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;

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

end

en{i,j}=ak;ien{i,j}=ek;

end

enden_bl{t}=en;

ienk{t}=ien;

alk{t}=al;ti(t)=toc;

end

close(h1)

disp('Encrypted Blocks')disp( en_bl)

if(isdir('en_frames'))

rmdir('en_frames','s');

endmkdir('en_frames');

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

strtemp1=strcat(pathname1,int2str(i),'.',pickind);

enp=en_bl{i};imwrite(cell2mat(enp),strtemp1);

end

name1='encrypted.avi';

aviobj = avifile(name1);path='en_frames\';

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

save fi1 filesave ti1 ti

save alk1 alk

save ftt fsave dcb dct_block

save cc c2

save mov1 mov

function pushbutton2_Callback(hObject, eventdata, handles)load alk1

load ftt

load dcbload cc

load mov1

pickind = 'tif';ii=decryp(alk,f,dct_block,c2);

if(isdir('de_frames'))

rmdir('de_frames','s');

end

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mkdir('de_frames');

pathname2= 'de_frames\';

for i=1:fstrtemp2=strcat(pathname2,int2str(i),'.',pickind);

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

endname2='decrypted.avi';

aviobj1 = avifile(name2);

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

for i=1:f

k1=mov{i};

k2=uint8(ii{i});er(i)=mean(mean(mean((k1-k2))))/100;

end

save er1 er

function pushbutton3_Callback(hObject, eventdata, handles)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')

function pushbutton4_Callback(hObject, eventdata, handles)close all;

clc;

subfunction.m:

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function dk=subfun(z,d4,a1)

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);

endif(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

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w=alk{t};

d2=dc{t};

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=1:3ui(:,:,p)=idct2(x(:,:,p));

end

id1{i,j}=ui;

elseid1{i,j}=d2{i,j};

end

end

endii{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.

4.Encrypted video

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The encrypted frames are converted to movie file format.

5.Encrypted frames:

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Images of encrypted frames.

6.Decrypted video

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The encrypted video is decrypted by reverse process of encryption.

7.Decrypted frames

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Images of the decrypted frames.

8.Comparison by Size

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The comparison is made between original video and encrypted video.

9.Time taken for encryption

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

10.Error for encryption

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The difference between original video and decrypted video is calculated.

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. 612

613.

[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.

novel video encryption

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